WO2025092309A1 - Method and apparatus for information processing, device, and storage medium - Google Patents

Abstract

According to embodiments of the present disclosure, provided are a method and apparatus for information processing, a device, and a storage medium. The method comprises: acquiring historical interaction information of a target object, the historical interaction information being generated on the basis of a group of interaction events between the target object and at least one service component; on the basis of the historical interaction information, determining a theme set of the group of interaction events; and, on the basis of the theme set, generating recommended content for the target object. Thus, a corresponding theme is generated on the basis of historical interaction information, and recommended content associated with the theme is generated. According to the embodiments of the present disclosure, the quality of recommended content can be improved.

Description

Method, device, equipment and storage medium for information processing

This application claims priority to the Chinese invention patent application entitled “Methods, devices, equipment and storage media for information processing” and application number 202311434431.4, filed on October 31, 2023, the entire contents of which are incorporated by reference into this application.

Technical Field

Example embodiments of the present disclosure generally relate to the field of computers, and more particularly, to methods, apparatuses, devices, and computer-readable storage media for information processing.

Background Art

With the rapid development of Internet technology, the Internet has become an important platform for people to obtain and share content. Users can access the Internet through terminal devices to enjoy various Internet services.

In addition, Internet platforms can also provide users with capabilities related to various types of information processing. How to improve the accuracy of such information processing has become the focus of people's attention.

Summary of the invention

In a first aspect of the present disclosure, a method for information processing is provided. The method comprises: obtaining historical interaction information of a target object, the historical interaction information being generated based on a set of interaction events between the target object and at least one business component; determining a set of topic sets of a set of interaction events based on the historical interaction information; and generating recommended content for the target object based on the topic set.

In a second aspect of the present disclosure, a method for information processing is provided. The method includes: obtaining first information associated with a target object; and providing recommended content to the target object based on the first information, wherein the recommended content includes at least one part organized based on at least one theme, each part includes at least one content item associated with the corresponding theme, and the at least one content item is generated based on at least historical interaction information within a preset period of time.

In a third aspect of the present disclosure, a method for information processing is provided. The method includes: obtaining second information associated with a target object; and providing recommended content to the target object based on the second information, wherein the recommended content includes a plurality of parts corresponding to different message classifications, each part includes a group of content items corresponding to a corresponding message classification, each content item is generated based on a group of unread messages of the target object, and the message classification indicates the importance level of the unread messages corresponding to the group of content items.

In a fourth aspect of the present disclosure, a device for information processing is provided. The device includes: a first acquisition module configured to acquire historical interaction information of a target object, where the historical interaction information is generated based on a set of interaction events between the target object and at least one business component; a theme determination module configured to determine a theme set of a set of interaction events based on the historical interaction information; and a content generation module configured to generate content based on the theme set. Become recommended content for the target audience.

In a fifth aspect of the present disclosure, a device for information processing is provided. The device includes: a second acquisition module configured to acquire first information associated with a target object; and a first providing module configured to provide recommended content to the target object based on the first information, wherein the recommended content includes at least one part organized based on at least one theme, each part includes at least one content item associated with the corresponding theme, and the at least one content item is generated based on at least historical interaction information within a preset period of time.

In a sixth aspect of the present disclosure, a device for information processing is provided. The device includes: a third acquisition module configured to acquire second information associated with a target object; and a second providing module configured to provide recommended content to the target object based on the second information, wherein the recommended content includes a plurality of parts corresponding to different message classifications, each part includes a group of content items corresponding to a corresponding message classification, each content item is generated based on a group of unread messages of the target object, and the message classification indicates the importance level of the unread messages corresponding to the group of content items.

In a seventh aspect of the present disclosure, an electronic device is provided. The device includes at least one processing unit; and at least one memory, the at least one memory is coupled to the at least one processing unit and stores instructions for execution by the at least one processing unit. When the instructions are executed by the at least one processing unit, the device executes the method of the first aspect, the second aspect, or the third aspect.

In an eighth aspect of the present disclosure, a computer-readable storage medium is provided, wherein a computer program is stored on the computer-readable storage medium, and the computer program can be executed by a processor to implement the method of the first aspect, the second aspect, or the third aspect.

It should be understood that the contents described in this content section are not intended to limit the key features or important features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, wherein:

FIG1 is a schematic diagram showing an example environment in which embodiments of the present disclosure can be implemented;

FIG2 shows a flow chart of a method for information processing according to some embodiments of the present disclosure;

FIG3 shows a flow chart of a method for information processing according to some embodiments of the present disclosure;

FIG4 illustrates an example interface according to some embodiments of the present disclosure;

FIG5 shows a flow chart of a method for information processing according to some embodiments of the present disclosure;

FIG6 illustrates an example interface according to some embodiments of the present disclosure;

7A, 7B and 7C show block diagrams of devices for information processing according to some embodiments of the present disclosure; and

FIG8 shows a block diagram of a device capable of implementing various embodiments of the present disclosure.

DETAILED DESCRIPTION

It is understandable that before using the technical solutions disclosed in the embodiments of the present disclosure, the types, scope of use, and usage scenarios of the information involved in the present disclosure should be informed to the relevant users in an appropriate manner in accordance with relevant laws and regulations, and the authorization of the relevant users should be obtained. The relevant users can include any type of right holders, such as individuals. People, companies, groups.

For example, in response to receiving an active request from a user, a prompt message is sent to the relevant user to clearly prompt the relevant user that the operation requested to be performed will require obtaining and using the relevant user's information. Thus, the relevant user can autonomously choose whether to provide information to the electronic device, application, server, storage medium, or other software or hardware that performs the operation of the technical solution of the present disclosure according to the prompt message.

As an optional but non-limiting implementation, in response to receiving an active request from a relevant user, the method of sending a prompt message to the relevant user may be, for example, a pop-up window, in which the prompt message may be presented in text form. In addition, the pop-up window may also carry a selection control for the user to select "agree" or "disagree" to provide personal information to the electronic device.

It is understandable that the above notification and the process of obtaining user authorization are merely illustrative and do not constitute a limitation on the implementation of the present disclosure. Other methods that meet the relevant laws and regulations may also be applied to the implementation of the present disclosure.

It is understandable that when adopting this technical solution, the data involved (including but not limited to the data itself, data acquisition, use, storage, and transmission) shall comply with the requirements of relevant laws, regulations and relevant provisions.

The term "in response to" as used herein refers to a state in which a corresponding event occurs or a condition is satisfied. It will be understood that the timing of executing a subsequent action executed in response to the event or condition is not necessarily strongly related to the time when the event occurs or the condition is satisfied. For example, in some cases, the subsequent action may be executed immediately when the event occurs or the condition is satisfied; while in other cases, the subsequent action may be executed some time after the event occurs or the condition is satisfied.

Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

It should be noted that the titles of any sections/subsections provided herein are not restrictive. Various embodiments are described throughout this article, and any type of embodiment may be included under any section/subsection. In addition, the embodiments described in any section/subsection may be combined in any manner with any other embodiments described in the same section/subsection and/or different sections/subsections.

In the description of the embodiments of the present disclosure, the term "including" and similar terms should be understood as open inclusion, that is, "including but not limited to". The term "based on" should be understood as "based at least in part on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The term "some embodiments" should be understood as "at least some embodiments". Other explicit and implicit definitions may be included below. The terms "first", "second", etc. may refer to different or the same objects. Other explicit and implicit definitions may be included below.

As used herein, the term "model" can learn the association between the corresponding input and output from the training data, so that the corresponding output can be generated for a given input after the training is completed. The generation and use of the model can be based on the technology permitted by laws and regulations such as machine learning, referred to as available technology. For example, deep learning is a machine learning algorithm that processes inputs and provides corresponding outputs by using multiple layers of processing units. In this article, "model" may also be referred to as "machine learning model", "machine learning network" or "network", and these terms are used interchangeably in this article. A model can also include different types of processing units or networks.

As briefly mentioned above, people can use various types of information processing tools to improve the efficiency of information processing. However, traditional information processing tools are difficult to provide users with recommended content that matches them, thus affecting Affects information processing efficiency.

Embodiments of the present disclosure provide a scheme for information processing. Specifically, historical interaction information of a target object (e.g., a user or an organization) may be obtained, wherein the historical interaction information is generated based on a set of interaction events between the target object and at least one business component (e.g., a digital assistant or other office component). Further, a set of topics for a set of interaction events may be determined based on the historical interaction information. Accordingly, recommended content for the target object may be generated based on the set of topics.

Therefore, by generating corresponding topics based on historical interaction information and generating recommended content associated with the topics, the embodiments of the present disclosure can improve the quality of recommended content.

Example embodiments of the present disclosure are described below with reference to the accompanying drawings.

Example Environment

Fig. 1 shows a schematic diagram of an example environment 100 in which embodiments of the present disclosure can be implemented. As shown in Fig. 1, in the environment 100, a terminal device 110 can be used to provide a digital assistant 102 for a target object 150. Such a target object may include a user or an organization, wherein the organization may be an enterprise, a group, a department, etc.

Exemplarily, such a digital assistant 102 may also be referred to as a digital assistant, or a digital robot. It should be understood that, although the digital assistant 102 is shown in FIG. 1 as being included in the terminal device 110, part of the processing capabilities of the digital assistant 102 may also be at least partially based on the server 120, for example. For example, the front-end portion of the digital assistant 102 (e.g., the portion for presentation) may be included in the terminal device 110, but the back-end portion of the digital assistant 102 (e.g., the portion for information processing) may be included in the server 120.

In some examples, the digital assistant 102 may be, for example, a digital assistant that assists the target object 150, such as office work, or may be any other appropriate entity form. The digital assistant 102 may also run independently or be integrated into a specific application.

In some embodiments, the digital assistant 102 can be enabled, for example, called or awakened, by an appropriate manner (e.g., a shortcut key, a button, or voice). If the digital assistant 102 is active, the terminal device 110 can present an interface 104 associated with the digital assistant 102. The interface 104 can be in the style of a conversational user interface (also referred to as a conversation interface or conversation window), or it can be any other appropriate interface form. As will be described in detail below, such an interface 104 can also include interface elements for information interaction, such as a message input box, a message list, a message bubble, and so on. Through the interface 104, the digital assistant 102 can provide content in an appropriate form to the target object 150, such as recommended content.

Furthermore, the server 120 may allow the target object 150 to interact with the digital assistant 102 to obtain information generated by the digital assistant 102. Alternatively, as will be described in detail below, with the authorization of the target object 150, the recommended content generated by the digital assistant 102 may also be based on the historical interaction between the target object 150 and at least one business component 115.

Such business components 115 may include components that can provide appropriate types of business services for the target object 150, examples of which may include but are not limited to: office components, tool components, etc. In some embodiments, such business components may be installed on the same terminal device 110. Alternatively or additionally, such business components may also be installed on other terminal devices, or provided in the form of cloud services.

In some embodiments, such business components 115 may include multiple office components in an office suite. An office suite may be a set of office components developed to improve office efficiency, such as office components for creating and editing documents. Components, office components for creating and editing tables, office components for drawing, and so on.

In some embodiments, the multiple office components include multiple items of the following: a chat component, a document component, an audio and video conferencing component, an email component, a calendar component, a schedule component, a task component, an Objectives and Key Results (OKR) component, and/or appropriate office components that are currently available or may be developed in the future.

In some embodiments, the digital assistant 102 may be a separate application from the business component 115. Alternatively, the digital assistant 102 may also be a function or component appropriately integrated into the business component 115.

In some embodiments, the historical interaction information 130 may be maintained in an appropriate electronic device as needed, such as the terminal device 110, the server 120, and/or other appropriate electronic devices. The historical interaction information 130 may include, for example, both interaction information stored on the terminal device 110 and interaction information uploaded to the server 120.

In some embodiments, the server 120 may determine a topic set 135 corresponding to the historical interaction event based on the analysis of the historical interaction information 130. Furthermore, the digital assistant 102 may also utilize the determined topic set 135 to interact with the target object 150.

As will be described in detail below, the topic set 135 can be provided for interaction between the digital assistant 102 and the target object 150. As an example, the server 120 can generate recommended content for the target object 150 based on the topic set 135, and the digital assistant 102 can provide it to the target object 150.

In some embodiments, the terminal device 110 communicates with the server 120 to provide services for the digital assistant 102. The terminal device 110 can be any type of mobile terminal, fixed terminal or portable terminal, including a mobile phone, a desktop computer, a laptop computer, a notebook computer, a netbook computer, a tablet computer, a media computer, a multimedia tablet, a personal communication system (PCS) device, a personal navigation device, a personal digital assistant (PDA), an audio/video player, a digital camera/camcorder, a positioning device, a television receiver, a radio broadcast receiver, an e-book device, a gaming device, or any combination of the foregoing, including accessories and peripherals of these devices or any combination thereof. In some embodiments, the terminal device 110 can also support any type of interface for the target object 150 (such as a "wearable" circuit, etc.). The server 120 can be various types of computing systems/servers that can provide computing capabilities, including but not limited to mainframes, edge computing nodes, computing devices in cloud environments, and the like.

Although only one server 120 is shown in FIG1 , the environment 100 may include multiple servers 120. For example, the historical interaction information 130 and/or the topic set 135 may be stored locally or in a second server 120 as needed and with relevant user authorization. It should be understood that this is only an exemplary description and does not imply any limitation on the scope of the present disclosure.

It should be understood that the structure and functionality of environment 100 are described for exemplary purposes only and does not imply any limitation on the scope of the present disclosure.

Example Process

FIG2 shows a flow chart of a process 200 for information processing according to some embodiments of the present disclosure. The process 200 may be implemented by an appropriate electronic device or a combination of electronic devices (e.g., the server 120, the terminal device 110, or a combination of the server 120 and the terminal device 110 in FIG1 ). For ease of description, the server 120 is taken as an example below, and the process 200 is described with reference to FIG1 .

In block 210 , the server 120 obtains historical interaction information 130 of a target object. The historical interaction information 130 is generated based on a set of interaction events between the target object 150 and at least one business component 115 .

In some embodiments, when target object 150 interacts with business component 115 , business component 115 may generate log records and send the log records to a logging module. Such a logging module may run at a suitable electronic device such as server 120 .

Further, the recording module can generate corresponding record entries based on the received log records and construct a record library. In some embodiments, such record entries may include knowledge elements (Knowledge) to describe business objects corresponding to historical interaction events. In some embodiments, the record library can be maintained in an appropriate electronic device, which can be stored at the terminal device 110, or stored at the server 120.

In some embodiments, such business objects may include business objects generated, edited, referenced, shared, etc. by the target object 150 during the interaction with the business component 115. Taking the business component 115 as a document component as an example, the historical interaction event may include a creation event of a specific document in the document component by the target object 150. Accordingly, the business object corresponding to the document creation event is the specific document.

In some embodiments, the knowledge element may be a natural language description of the business object, which is intended to abstract and/or compress the content of the business object. For example, taking a document object as an example of a business object, the knowledge element may be used to describe the subject, completion status, audience, language, expression style, etc. of the document object.

It should be understood that information of different dimensions can be selected according to the type of business object to generate knowledge elements for describing the business object. For example, taking a conversation as an example of a business object, the knowledge element can be used to describe the type of conversation (e.g., whether it is a one-on-one chat), the overview of the conversation, etc.

Therefore, by maintaining knowledge elements in record entries, embodiments of the present disclosure can describe or characterize the business objects involved in the corresponding historical interaction events through limited content length.

In some embodiments, the record entry may also include a time element for indicating the time of occurrence of the historical interaction event. For example, continuing to use the creation of a document as an example of a historical interaction event, such a time element may, for example, indicate the creation time of the document.

In some other embodiments, the record entry may also include an action element for indicating the event type of the historical interaction event. Continuing to use the creation of a document as an example of a historical interaction event, such an action element may, for example, indicate that the type of the historical interaction event is a "create" type.

In some embodiments, the record entry may also include a payload element for indexing a business object corresponding to the corresponding historical interaction event. Taking a document as an example of a business object, the payload element may include, for example, a document number or a document identifier for indexing the document.

Thus, in some scenarios, after the target object 150 interacts with the business component 115, the recording module 210 can generate a corresponding record entry. Such a record entry can be represented as {time element, action element, knowledge element, load element}, for example, to describe the historical interaction event from multiple preset dimensions. Such a record entry can also be called historical interaction information 130 corresponding to the interaction event.

In block 220 , the server 120 determines a topic set 135 for a set of interaction events based on the historical interaction information 130 .

In some embodiments, the server 120 may use the target processing entity to determine the topic set 135. Specifically, the server 120 may provide at least the knowledge elements and action elements in the historical interaction information 130 to the target processing entity so that the target processing entity can perform clustering processing on the historical interaction information 130.

It should be understood that the target processing entity may be a processing entity based on appropriate information processing technology, and may implement one or more functions such as text generation, image generation, summarization, encoding, translation, chatbot, etc. The target processing entity may also be any other appropriate entity form. In some examples, the target processing entity may be, for example, Language models may be included.

Exemplarily, the target processing entity (eg, language model) may be based on a semantic analysis of each action element and knowledge element in the historical interaction information to obtain a plurality of topics through clustering.

In some embodiments, at least one business component may include, for example, an office component used by the target object 150 in work. Accordingly, the subject determined by the target processing entity may also be, for example, the subject of the work content (eg, project name, etc.).

Further, the server 120 may obtain a topic set determined by the target processing entity based on the knowledge element and the action element. Exemplarily, continuing to take the topic of the work content as an example, such a topic set may include, for example, "Project X", "Project Y", etc. In some embodiments, if the historical interaction information corresponding to some interaction events cannot be clustered into such a topic, it may also be clustered into a preset category, for example, "others".

In some embodiments, the server 120 may, for example, periodically trigger analysis of the historical interaction information 130 to determine the corresponding topic set 135. For example, the server 120 may trigger full analysis of the historical interaction information 130 every two weeks to determine the corresponding topic set, for example, using the target processing entity.

In some embodiments, the server 120 may also process the newly acquired historical interaction information by merging clusters. For example, when the topic set 135 has been determined based on the first historical interaction information within a first time period (e.g., before yesterday), the server 120 may also obtain the second historical interaction information of the target object 150. Such second historical interaction information may be generated based on a group of interaction events (also referred to as a second group of interaction events) within a second time period (e.g., yesterday).

Accordingly, the server 120 may, for example, determine the matching degree between the second group of interaction events and the topics in the topic set in the topic set. Continuing with the example that the topic set includes "Project X", "Project Y" and "Others", the server 120 may, for example, determine the matching degree between such second group of interaction events and "Project X" or "Project Y" based on the historical interaction information corresponding to the second group of interaction events.

Exemplarily, the server 120 may determine the degree of matching by providing the target processing entity with information such as knowledge elements and action elements of historical interaction information corresponding to the second group of interaction events.

Further, the server 120 may determine the association between the second group of interaction events and the topic set based on the matching degree.

Specifically, in response to the first interaction event in the second group of interaction events having a matching degree with the target topic in the topic set reaching a threshold, the server 120 may associate the first interaction event with the target topic. For example, if a certain event in the second group of interaction events has a matching degree with "Project X" reaching a threshold, the historical interaction information corresponding to the interaction event may be marked as being associated with "Project X".

In response to the second interaction event in the second group of interaction events having a matching degree with a theme other than the preset theme in the theme set being less than a threshold, the second interaction event is associated with the preset theme. For example, if a certain event in the second group of interaction events has a matching degree with both "Project X" and "Project Y" being less than a threshold, the historical interaction information corresponding to the interaction event may be marked as being associated with the preset theme "Others".

In some embodiments, in response to the number of multiple interaction events associated with a preset topic (e.g., "others") reaching a preset number, the server 120 may trigger a re-clustering process. For example, the server 120 may determine at least one topic based on historical interaction information corresponding to multiple interaction events associated with the preset topic. For example, if the number of events included in the topic "others" exceeds a threshold number, the server 120 may, for example, use a target processing entity to re-cluster the events in the topic to determine one or more new topics. Further, the server 120 may update the topic set 135 using the determined at least one topic.

Based on this approach, the embodiments of the present disclosure can cluster corresponding topics according to the historical interactions between the target object and the business component, thereby facilitating the sorting out of the historical interactions of the target object.

At block 230 , the server 120 generates recommended content for the target object 150 based on the topic set 135 .

In some embodiments, the server 120 may construct a set of topic objects associated with a set of topics in the topic set 135. Furthermore, the server 120 may also generate recommended content for the target object 150 based on the attributes of the set of topic objects.

In certain embodiments, each theme object may include multiple attributes. In certain embodiments, the theme object may have a corresponding text mark, such as "X Project". Such a text mark may help the target object to intuitively understand the content involved in the theme.

In some embodiments, the subject object may have a corresponding color identification. For example, different subjects may be associated with different color identifications.

In some embodiments, the subject object may also record entities associated with the subject, for example. Such entities may include, but are not limited to, users, sessions, documents, messages, meetings, etc. For example, the server 120 may determine entities associated with the subject based on the association between the subject and the knowledge element.

In some embodiments, the subject object may also record action clustering information, for example. The action clustering information may be generated, for example, based on the action elements of multiple interactive events associated with the subject. Exemplarily, the server 120 may provide the target processing entity with the action elements of multiple interactive events associated with a specific subject, and may generate corresponding action clustering information. Such action clustering information may be used, for example, to concisely describe the main events under the subject.

In some embodiments, the subject object may also record knowledge clustering information, for example. The knowledge clustering information may be generated based on the knowledge elements of multiple interaction events associated with the subject. Exemplarily, the server 120 may provide the target processing entity with the knowledge elements of multiple interaction events associated with a specific subject, and may generate corresponding knowledge clustering information. Such knowledge clustering information may be used, for example, to concisely describe the key points, to-do items, unread messages, etc. under the subject.

In some embodiments, the subject object may also record status information of the subject, for example. The status information may indicate the urgency of the subject, for example. In some embodiments, the server 120 may determine the urgency of each subject, for example, according to a preset urgency judgment rule. Alternatively, the server 120 may also use a machine learning model to determine the corresponding urgency based on the relevant description information of each subject.

Based on this approach, the server 120 can utilize structured data such as subject objects to effectively manage historical interactions of the target object, so as to facilitate the target object to review or make targeted recommendations for the target object.

In some embodiments, the recommended content generated by the server 120 based on the theme set 135 may include, for example, structured content associated with a specific period of time, wherein the structured content is used to describe the interactive events within the specific period of time. As will be described in detail below, in some scenarios, the structured content may include, for example, a work summary associated with a specific period of time. Such a work summary may include, for example, multiple content parts corresponding to different themes in the theme set.

As will be described in detail below, in some scenarios, the recommended content may include message summary content indicating the importance level of a group of messages associated with the target object. In some examples, the group of messages includes unread messages of the target object 150. As will be described below with reference to Figures 5 to 6, such recommended content may, for example, include a summary of unread messages about the target object 150.

In some other embodiments, the recommended content generated by the server 120 based on the topic set 135 may also include, for example, summary content associated with a specific entity. For example, the server 120 may organize information for the target object based on the topic set 135 to generate an organization of group chat content, an organization of document content, an organization of conference content, etc.

In some embodiments, the recommended content generated by the server 120 based on the topic set 135 may also include, for example, to-do content for the target object 150. For example, the server 120 may recommend creating a to-do task based on the commitment of the target object 150 in the conversation.

In some embodiments, the recommended content generated by the server 120 based on the theme set 135 may also include reminder content for the target object. Such reminder content may include any appropriate form, such as alarm reminder, schedule reminder, task reminder, etc.

In some embodiments, such recommended content may be actively generated and pushed by the server 120, for example. Alternatively, it may be generated in response to an interactive request of the target object 150 (for example, requesting a digital assistant to generate a work summary).

Based on this approach, the embodiments of the present disclosure can determine the corresponding topic based on the analysis of the historical interaction events of the target object, so as to provide the target object with recommended content based on the topic, thereby improving the efficiency of content recommendation.

The following will describe example recommended content of some embodiments of the present disclosure with reference to FIG3 and FIG4. FIG3 shows a flowchart of a process 300 for information processing according to some embodiments of the present disclosure. The process 300 can be implemented by an appropriate electronic device or a combination of electronic devices (for example, the terminal device 110, the server 120, or the combination of the server 120 and the terminal device 110 in FIG1). For the convenience of description, the following takes the terminal device 110 as an example and describes the process 300 with reference to FIG1.

As shown in the figure, at block 310, the terminal device 110 obtains first information associated with the target object 150. In some embodiments, after generating the recommended content based on the process discussed above, the server 120 may send the first information associated with the recommended content to the target object 150. Such first information may include the recommended content, or may be used for presenting the corresponding recommended content by the terminal device 110.

In box 320, the terminal device 110 provides recommended content to the target object 150 based on the first information, wherein the recommended content includes at least one part organized based on at least one theme, each part includes at least one content item associated with the corresponding theme, and the at least one content item is generated based on at least historical interaction information within a preset time period.

The specific process of block 320 will be described below with reference to Fig. 4. Fig. 4 shows an example interface 400 according to some embodiments of the present disclosure. The interface 400 may be provided by the terminal device 110, for example.

As shown in Fig. 4, the terminal device 110 may provide recommended content 405. As described with reference to Fig. 2, such recommended content 405 may be generated by the server 120 based on historical interaction information within a preset period of time.

Further, taking FIG. 4 as an example, the recommended content 405 may include a plurality of sections organized based on a plurality of topics (ie, topic 410 , topic 420 , and topic 430 ).

Taking the part corresponding to the theme 410 as an example, the part may include multiple content items, such as content item 412, content item 416, etc. Such at least one content item may be generated by the server 120 based on the theme object introduced above. For example, the server 120 may generate such a content item based on the behavior clustering information and/or knowledge clustering information in the theme object.

In some embodiments, taking topic 410 as an example, at least one content item associated with topic 410 may be The first type of content item (e.g., content item 412) can be used to indicate the things that the target object has completed with respect to the corresponding topic. As shown in FIG. 4, content item 412 can belong to the category of "important conclusions" to indicate the main things that have been completed with respect to the topic 410.

In some embodiments, taking topic 410 as an example, at least one content item associated with topic 410 may include a second type of content item. The second type of content item (e.g., content item 416) may be used to indicate matters to be completed by target object 150 regarding topic 410. As shown in FIG. 4 , content item 412 may belong to the category of “to-do items” to indicate matters to be completed subsequently regarding topic 410.

Similarly, the parts corresponding to other topics 420 and/or topic 430 may also have corresponding one or more content items. For such content items, reference may be made to the description of topic 310, which will not be repeated here.

In some embodiments, in response to receiving a first operation on a first type of content item, the terminal device 110 may present a first interface of a target business component. The first interface may be used to display information about historical interaction events between a target object and the target business component, the historical interaction events corresponding to the first type of content item.

As shown in FIG4 , the terminal device 110 may also display a viewing entry 414 in association with a first type of content item (e.g., content item 412). Upon receiving a selection of the viewing entry 414, the terminal device 110 may, for example, jump to an interface of a business component (e.g., a conversation component) corresponding to the content item 412 to indicate information about a historical interaction event between the target object 150 and the conversation component corresponding to the content item 412. Such information may, for example, be a historical message input by the target object 150 in the conversation component.

In this way, the embodiments of the present disclosure can further facilitate the target object to obtain original information related to the content item, thereby improving the efficiency of the target object in obtaining information.

In some embodiments, in response to receiving a second operation for a second type of content item, the terminal device 110 may create a task associated with the to-be-done item. Exemplarily, as shown in FIG4B , the terminal device 110 may also provide a creation portal 418 in association with the content item 416. Upon receiving a selection for the creation portal 418, the terminal device 110 may, for example, create a corresponding to-be-done task based on the content item 416.

In this way, the embodiment of the empty cover can facilitate the target object to better sort out and plan future to-do items, thereby improving the efficiency of item management.

In some embodiments, the terminal device 110 may also support the target object 150 to modify the information of the subject presented in the recommended content 405. For example, the terminal device 110 may receive the editing operation of the target object 150 on the subject 410, and may update the identification of the target object 150 accordingly. Such identification may include a text identification (e.g., a subject name), a color identification (e.g., a color corresponding to the subject), or an image identification (e.g., a picture corresponding to the subject). For example, the target object 150 may modify the text identification of the subject 410 to modify it from the text "X project" to "XX project". Such a modification may be used, for example, to update the subject object corresponding to the subject 410, so that it can be used for the subsequent generation and presentation of other recommended content.

In some embodiments, the terminal device 110 may also identify business objects included in content items (eg, content item 412 and/or content item 416 ), and may display such business objects in a target style (eg, a blue link style).

Further, after receiving the third operation on the business object in the content item, the terminal device 110 can present the second interface associated with the business object accordingly. For example, if the content item 412 includes a contact, the target object 150 can jump to the conversation interface corresponding to the contact by clicking the blue link of the contact. As another example, if the content item includes a document, the target object 150 can jump to the viewing interface of the document by clicking the blue link of the document.

In some embodiments, as shown in FIG. 4 , the digital assistant may provide recommended content 405 to the target object 150 during a conversation between the target object 150 and the digital assistant.

In some embodiments, the terminal device 110 may also support, for example, generating a document corresponding to the recommended content 405. Based on the fourth operation for the recommended content, the terminal device 110 may create a target document. The target document may contain at least part of the recommended content. For example, the terminal device 110 may provide an entry for creating a document, and after receiving a selection of the entry, the terminal device 110 may automatically generate a local document or a cloud document corresponding to the recommended content 405.

In some embodiments, as described above, the recommended content 405 shown in FIG. 4 may be, for example, a work summary of the target object within a preset period of time, such as a daily work summary, a weekly work summary, and the like.

As shown in Fig. 4, in some embodiments, the terminal device 110 may also present a first subscription entry 440 in association with the recommended content 405. Further, based on the selection of the first subscription entry 440, the terminal device 110 may periodically provide the target object with recommended content corresponding to the corresponding time period.

For example, when the target object 150 subscribes to recommended content (eg, daily work summary) through the first subscription portal 440, the terminal device 110 may provide the target object 150 with the previous day's work summary periodically (eg, at a predetermined time every morning).

Further, in the case where the target object has subscribed to the recommended content, the terminal device 110 may, for example, present a first unsubscribe entry in association with the recommended content corresponding to the corresponding time period. Accordingly, based on the selection of the first unsubscribe entry, the terminal device 110 may stop providing the target object 150 with the recommended content corresponding to the subsequent time period.

Continuing with the daily work summary as an example, for the daily work summary received subsequently, the target object can, for example, trigger the terminal device 110 to stop providing such daily work summary by clicking on the corresponding unsubscribe entry.

Based on the process described above, the embodiments of the present disclosure can provide the target object with recommended content determined based on historical interaction information, and enable such recommended content to be organized based on one or more topics, thereby greatly improving the intuitiveness of the recommended content and thus improving the usability of such recommended content for the target object.

The following will describe example recommended content of some embodiments of the present disclosure with reference to FIG5 and FIG6. FIG5 shows a flowchart of a process 500 for information processing according to some embodiments of the present disclosure. The process 500 can be implemented by an appropriate electronic device or a combination of electronic devices (for example, the terminal device 110, the server 120, or the combination of the server 120 and the terminal device 110 in FIG1). For the convenience of description, the following takes the terminal device 110 as an example and describes the process 500 with reference to FIG1.

As shown in the figure, at block 510, the terminal device 110 obtains the second information associated with the target object 150. In some embodiments, after generating the recommended content based on the process discussed above, the server 120 may send the second information associated with the recommended content to the target object 150. Such second information may include the recommended content, or may be used for presenting the corresponding recommended content by the terminal device 110.

In box 520, the terminal device 110 provides recommended content to the target object 150 based on the second information, wherein the recommended content includes multiple parts corresponding to different message classifications, each part includes a group of content items corresponding to the corresponding message classification, each content item is generated based on a group of unread messages of the target object, and the message classification indicates the importance level of the unread messages corresponding to the group of content items.

The specific process of block 520 will be described below with reference to Fig. 6. Fig. 6 shows an example interface 600 according to some embodiments of the present disclosure. The interface 600 may be provided by the terminal device 110, for example.

As shown in Fig. 6, the terminal device 110 can provide recommended content 605, and the recommended content 605 can include multiple parts corresponding to different message classifications. Exemplarily, such message classifications can include a first classification 610 (e.g., "important unread") and a second classification 640 (e.g., "unimportant unread") corresponding to different importance levels.

Furthermore, each message category may include a corresponding set of content items, such as content item 620. Such content item 620 may be generated based on one or more dimension messages of target object 150.

Based on this approach, the embodiments of the present disclosure can intuitively sort out the unread messages for the target object based on the importance of the unread messages, thereby improving the efficiency of the target object in processing messages.

Further, as shown in Fig. 6, the terminal device 110 may also be associated with a group of content items to present an identification of a conversation corresponding to unread messages associated with a group of content items. For example, the terminal device 110 may indicate that the content item 620 corresponds to the conversation 615 (e.g., "Group X"). Additionally, the terminal device 110 may also display a group of content items corresponding to the conversation 635 (e.g., "Group Y") to indicate unread important messages in the conversation 635.

In some embodiments, based on the fifth operation for a group of content items, the terminal device 110 may present a viewing interface of a target conversation, wherein the target conversation corresponds to unread messages associated with a group of content items. Taking FIG. 6 as an example, the terminal device 110 may also provide a viewing entry 625 corresponding to a group of content items 620 under the conversation 615. When the target object selects the viewing entry 625, the terminal device 110 may present a viewing interface of the conversation 615 accordingly. The viewing interface may display one or more unread messages under the conversation, for example.

In some embodiments, based on the sixth operation for a group of content items, the terminal device 110 may mark the unread messages associated with the group of content items as read. Taking FIG. 6 as an example, the terminal device 110 may also provide a clear entry 630 corresponding to the next group of content items 620 of the conversation 615. When the target object selects the clear entry 630, the terminal device 110 may mark one or more unread messages corresponding to the group of content items 620 as read.

In some embodiments, the importance level of the unread message is determined by processing a set of descriptive information associated with the unread message using a first model. Exemplarily, such a first model may correspond to the target processing entity introduced above, and the server 120 may determine whether the unread message is an important message by providing the descriptive information of the unread message to the target processing entity.

In some embodiments, a content item (e.g., content item 620) may be generated by processing at least one unread message with the same importance level using a second model. Exemplarily, such a first model may correspond to the target processing entity introduced above, and the server 120 may provide the target processing entity with multiple messages classified as important unread messages in the session, so as to generate a group of content items 620 corresponding to the multiple messages using the target processing entity.

6, in some embodiments, the terminal device 110 may also present a second subscription entry 645 in association with the recommended content 605. Further, based on the selection of the second subscription entry 645, the terminal device 110 may periodically provide the target object with recommended content corresponding to the corresponding time period.

For example, when the target object 150 subscribes to recommended content (e.g., daily unread message summary) through the second subscription entry 645, the terminal device 110 can, for example, periodically (e.g., at a predetermined time every morning) provide the target object 150 with a summary of the previous day's unread messages.

Further, in the case where the target object has subscribed to the recommended content, the terminal device 110 may, for example, present a second unsubscribe entry in association with the recommended content corresponding to the corresponding time period. Accordingly, based on the selection of the second unsubscribe entry, the terminal device 110 may stop providing the target object 150 with the recommended content corresponding to the subsequent time period.

Continuing with the unread message summary as an example, for the unread message summary received subsequently, the target object can, for example, trigger the terminal device 110 to stop providing such daily unread message summary by clicking on the corresponding unsubscribe entry.

Based on the process described above, the embodiment of the present disclosure can provide the target object with sorting of unread messages, thereby improving the efficiency of the target object in processing messages.

Example devices and equipment

7A shows a schematic structural block diagram of an apparatus 400 for information processing according to some embodiments of the present disclosure. The apparatus 700A may be implemented as or included in the server 120, the terminal device 110, or a combination of the server 120 and the terminal device 110 in FIG. 1 . Each module/component in the apparatus 700A may be implemented by hardware, software, firmware, or any combination thereof.

As shown in the figure, the device 700A includes a first acquisition module 710, which is configured to acquire historical interaction information of the target object, where the historical interaction information is generated based on a set of interaction events between the target object and at least one business component; a topic determination module 720, which is configured to determine a topic set of a set of interaction events based on the historical interaction information; and a content generation module 730, which is configured to generate recommended content for the target object based on the topic set.

In some embodiments, the historical interaction information includes at least a knowledge element and an action element, wherein the knowledge element is used to describe a business object associated with a corresponding interaction event, and the action element is used to describe an event type of the corresponding interaction event.

In some embodiments, the historical interaction information further includes: a time element for indicating the time of occurrence of the interaction event; and/or a load element for indexing a business object associated with the interaction event.

In some embodiments, the topic determination module 720 is further configured to: provide at least knowledge elements and action elements in the historical interaction information to the target processing entity; and obtain a topic set determined by the target processing entity based on the knowledge elements and action elements.

In some embodiments, the historical interaction information is first historical interaction information associated with a first time period, a group of interaction events is a first group of interaction events, and the device 700A includes an association determination module, which is configured to: obtain second historical interaction information of the target object, wherein the second historical interaction information is generated based on a second group of interaction events within a second time period; determine the degree of match between the second group of interaction events and the topics in the topic set; and based on the degree of match, determine the association between the second group of interaction events and the topic set.

In some embodiments, the association determination module is further configured to: in response to the first interaction event in the second group of interaction events having a matching degree with the target topic in the topic set reaching a threshold, associate the first interaction event with the target topic; or in response to the second interaction event in the second group of interaction events having a matching degree with topics in the topic set other than the preset topic that is less than a threshold, associate the second interaction event with the preset topic.

In some embodiments, device 700A also includes a theme update module, which is configured to: in response to the number of multiple interaction events associated with a preset theme reaching a preset number, determine at least one theme based on historical interaction information corresponding to the multiple interaction events; and update the theme collection using the at least one theme.

In some embodiments, the content generation module 730 is further configured to: construct a set of topic objects associated with a set of topics in the topic set; and generate recommended content for the target object based on the attributes of the set of topic objects.

In some embodiments, the attributes include at least one of the following: a text identifier of the topic, a color identifier of the topic, an entity associated with the topic, action clustering information generated based on action elements of multiple interaction events associated with the topic, knowledge clustering information generated based on knowledge elements of multiple interaction events associated with the topic, and status information of the topic indicating the urgency of the topic.

In some embodiments, the recommended content includes structured content associated with a specific time period, where the structured content is used to describe interaction events within the specific time period.

In some embodiments, the structured content includes a summary of work associated with a particular time period.

In some embodiments, the recommended content includes message summary content indicating an importance level of a group of messages associated with the target object.

In some embodiments, the group of messages includes unread messages by the target object.

In some embodiments, the recommended content includes at least one of the following: summary content associated with a specific entity, to-do content for a target object, and reminder content for a target object.

7B shows a schematic structural block diagram of an apparatus 400 for information processing according to some embodiments of the present disclosure. Apparatus 700B may be implemented as or included in the server 120, terminal device 110, or a combination of the server 120 and the terminal device 110 in FIG. 1 . Each module/component in apparatus 700B may be implemented by hardware, software, firmware, or any combination thereof.

As shown in the figure, the device 700B includes a second acquisition module 740, which is configured to acquire first information associated with the target object; and a first provision module 750, which is configured to provide recommended content to the target object based on the first information, wherein the recommended content includes at least one part organized based on at least one theme, each part includes at least one content item associated with the corresponding theme, and the at least one content item is generated based on at least historical interaction information within a preset time period.

In some embodiments, at least one content item is generated based on historical interaction information corresponding to multiple interaction events associated with the target topic, wherein the historical interaction information includes at least knowledge elements and action elements, the knowledge elements are used to describe the business objects associated with the corresponding interaction events, and the action elements are used to describe the event type of the corresponding interaction events.

In some embodiments, at least one content item associated with the corresponding topic includes: a first type of content item indicating what the target object has completed regarding the corresponding topic; and/or a second type of content item indicating what the target object needs to complete regarding the corresponding topic.

In some embodiments, the device 700B also includes an interface presentation module, which is configured to: in response to receiving a first operation on a first type of content item, present a first interface of the target business component, wherein the first interface is used to display information about historical interaction events between the target object and the target business component, and the historical interaction events correspond to the first type of content item.

In some embodiments, the apparatus 700B further includes a task creation module configured to: in response to receiving a second operation on the second type of content item, create a task associated with the to-be-completed item.

In some embodiments, the device 700B further includes an identification updating module configured to update an identification of at least one subject based on an editing operation of the target object, where the identification includes a text identification, a color identification, or an image identification.

In some embodiments, the business object in at least one content item is displayed in a target style, and the apparatus 700 further includes a second interface presentation module configured to present a second interface associated with the business object based on a third operation on the business object.

In some embodiments, the first providing module 750 is further configured to: in a conversation with the digital assistant, the digital assistant provides recommended content to the target object.

In some embodiments, the apparatus 700B further includes a document creation module configured to: create a target document based on a fourth operation on the recommended content, wherein the target document includes at least a portion of the recommended content.

In some embodiments, the recommended content is a summary of the target object's work within a preset time period.

In some embodiments, the device 700B also includes a first subscription module configured to: present a first subscription entry in association with the recommended content; and periodically provide the target object with recommended content corresponding to the corresponding time period based on a selection of the first subscription entry.

In some embodiments, the device 700B also includes a first unsubscribe module configured to: present a first unsubscribe entry in association with the recommended content corresponding to the corresponding time period; and stop providing the recommended content corresponding to the subsequent time period to the target object based on the selection of the first unsubscribe entry.

7C shows a schematic structural block diagram of an apparatus 400 for information processing according to some embodiments of the present disclosure. Apparatus 700C may be implemented as or included in the server 120, terminal device 110, or a combination of the server 120 and the terminal device 110 in FIG. 1 . Each module/component in apparatus 700C may be implemented by hardware, software, firmware, or any combination thereof.

As shown in the figure, the device 700C includes a third acquisition module 760, which is configured to acquire second information associated with the target object; and a second provision module 770, which is configured to provide recommended content to the target object based on the second information, wherein the recommended content includes multiple parts corresponding to different message classifications, each part includes a group of content items corresponding to the corresponding message classification, each content item is generated based on a group of unread messages of the target object, and the message classification indicates the importance level of the unread messages corresponding to the group of content items.

In some embodiments, the apparatus 700C further comprises a conversation presentation module configured to: present, in association with a group of content items, an identifier of a conversation corresponding to unread messages associated with the group of content items.

In some embodiments, the device 700C also includes a conversation third interface presentation module, which is configured to: based on a fifth operation on a group of content items, present a viewing interface of a target conversation, wherein the target conversation corresponds to unread messages associated with the group of content items.

In some embodiments, the apparatus 700C further includes a message marking module configured to: based on a sixth operation on a group of content items, mark unread messages associated with the group of content items as read.

In some embodiments, the importance level of the unread message is determined by processing a set of descriptive information associated with the unread message using a first model.

In some embodiments, the content item is generated by processing at least one unread message having the same importance level using a second model.

In some embodiments, the device 700C also includes a second subscription module configured to present a second subscription entry in association with the recommended content; and based on the selection of the second subscription entry, periodically provide the target object with recommended content corresponding to the corresponding time period.

In some embodiments, the device 700C also includes a second unsubscribe module, which is configured to present a second unsubscribe entry in association with the recommended content corresponding to the corresponding time period; and based on the selection of the second unsubscribe entry, stop providing the recommended content corresponding to the subsequent time period to the target object.

FIG8 shows a block diagram of an electronic device 800 in which one or more embodiments of the present disclosure may be implemented. It should be understood that the electronic device 800 shown in FIG8 is merely exemplary and should not constitute any limitation on the functionality and scope of the embodiments described herein. The electronic device 800 shown in FIG8 may be used to implement the server 120, the terminal device 110, or a combination of the server 120 and the terminal device 110 of FIG1.

As shown in Fig. 8, electronic device 800 is in the form of a general electronic device. Components of electronic device 800 may include, but are not limited to, one or more processors or processing units 810, memory 820, storage device 830, one or more communication units 840, one or more input devices 850, and one or more output devices 860. Processing unit 810 may be an actual or virtual processor and is capable of performing various processes according to a program stored in memory 820. In a multi-processor system, multiple processing units execute computer executable instructions in parallel to improve the parallel processing capability of the electronic device 800.

The electronic device 800 typically includes a plurality of computer storage media. Such media can be any accessible media that can be obtained by the electronic device 800, including but not limited to volatile and non-volatile media, removable and non-removable media. The memory 820 can be a volatile memory (e.g., a register, a cache, a random access memory (RAM)), a non-volatile memory (e.g., a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), flash memory), or some combination thereof. The storage device 830 can be a removable or non-removable medium, and can include a machine-readable medium, such as a flash drive, a disk, or any other medium, which can be used to store information and/or data and can be accessed within the electronic device 800.

The electronic device 800 may further include additional removable/non-removable, volatile/non-volatile storage media. Although not shown in FIG. 8 , a disk drive for reading or writing from a removable, non-volatile disk (e.g., a “floppy disk”) and an optical drive for reading or writing from a removable, non-volatile optical disk may be provided. In these cases, each drive may be connected to a bus (not shown) by one or more data media interfaces. The memory 820 may include a computer program product 825 having one or more program modules configured to perform various methods or actions of various embodiments of the present disclosure.

The communication unit 840 implements communication with other electronic devices through a communication medium. Additionally, the functions of the components of the electronic device 800 can be implemented with a single computing cluster or multiple computing machines that can communicate through a communication connection. Therefore, the electronic device 800 can operate in a networked environment using a logical connection with one or more other servers, a network personal computer (PC), or another network node.

The input device 850 may be one or more input devices, such as a mouse, a keyboard, a tracking ball, etc. The output device 860 may be one or more output devices, such as a display, a speaker, a printer, etc. The electronic device 800 may also communicate with one or more external devices (not shown) through the communication unit 840 as needed, such as a storage device, a display device, etc., communicate with one or more devices that allow a user to interact with the electronic device 800, or communicate with any device that allows the electronic device 800 to communicate with one or more other electronic devices (e.g., a network card, a modem, etc.). Such communication may be performed via an input/output (I/O) interface (not shown).

According to an exemplary implementation of the present disclosure, a computer-readable storage medium is provided, on which computer-executable instructions are stored, wherein the computer-executable instructions are executed by a processor to implement the method described above. According to an exemplary implementation of the present disclosure, a computer program product is also provided, which is tangibly stored on a non-transitory computer-readable medium and includes computer-executable instructions, and the computer-executable instructions are executed by a processor to implement the method described above.

Various aspects of the present disclosure are described herein with reference to the flowcharts and/or block diagrams of the methods, devices, equipment, and computer program products implemented according to the present disclosure. It should be understood that each box in the flowchart and/or block diagram and the combination of each box in the flowchart and/or block diagram can be implemented by computer-readable program instructions.

These computer-readable program instructions can be provided to a processing unit of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processing unit of the computer or other programmable data processing device, a device that implements the functions/actions specified in one or more boxes in the flowchart and/or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions make the computer, programmable data processing device, and/or other equipment work in a specific way. Therefore, the computer-readable medium storing the instructions includes a manufactured product, which includes implementing the flowchart and/or block diagram. Instructions for various aspects of the functions/actions specified in one or more boxes.

Computer-readable program instructions can be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operational steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, so that the instructions executed on the computer, other programmable data processing apparatus, or other device implement the functions/actions specified in one or more boxes in the flowchart and/or block diagram.

The flow chart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to multiple implementations of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a part of a module, program segment or instruction, and a part of a module, program segment or instruction includes one or more executable instructions for realizing the logical function of the specification. In some implementations as replacements, the function marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two continuous square boxes can actually be executed substantially in parallel, and they can sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each square box in the block diagram and/or flow chart, and the combination of the square boxes in the block diagram and/or flow chart can be realized by a special hardware-based system that performs the function or action of the specification, or can be realized by a combination of special hardware and computer instructions.

The above descriptions of various implementations of the present disclosure are exemplary, non-exhaustive, and not limited to the disclosed implementations. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described implementations. The selection of terms used herein is intended to best explain the principles of the implementations, practical applications, or improvements to the technology in the market, or to enable other persons of ordinary skill in the art to understand the various implementations disclosed herein.

Claims (39)

An information processing method, comprising: Acquire historical interaction information of a target object, where the historical interaction information is generated based on a set of interaction events between the target object and at least one business component; Based on the historical interaction information, determining a topic set of the group of interaction events; and Based on the topic set, recommended content for the target object is generated. According to the method according to claim 1, the historical interaction information at least includes knowledge elements and action elements, the knowledge elements are used to describe the business objects associated with the corresponding interaction events, and the action elements are used to describe the event types of the corresponding interaction events. The method according to claim 2, wherein the historical interaction information further comprises: A time element, used to indicate the time when the interaction event occurs; and/or The payload element is used to index the business object associated with the interaction event. The method according to claim 2, wherein determining a topic set of the set of interaction events based on the historical interaction information comprises: providing at least the knowledge element and the action element in the historical interaction information to a target processing entity; and The topic set determined by the target processing entity based on the knowledge elements and the action elements is obtained. The method according to claim 1, wherein the historical interaction information is first historical interaction information associated with a first time period, and the group of interaction events is a first group of interaction events, the method further comprising: Acquire second historical interaction information of the target object, wherein the second historical interaction information is generated based on a second group of interaction events within a second time period; Determining a degree of match between the second group of interaction events and a topic in the topic set; and Based on the matching degree, an association between the second group of interaction events and the topic set is determined. The method according to claim 5, wherein determining the association between the second group of interaction events and the set of topics comprises: In response to the matching degree between a first interaction event in the second group of interaction events and a target topic in the topic set reaching a threshold, associating the first interaction event with the target topic; or In response to the matching degree between a second interaction event in the second group of interaction events and a theme other than a preset theme in the theme set being less than a threshold, the second interaction event is associated with the preset theme. The method according to claim 6, further comprising: In response to the number of the plurality of interaction events associated with the preset theme reaching a preset number, determining at least one theme based on historical interaction information corresponding to the plurality of interaction events; and The topic set is updated using the at least one topic. The method according to claim 1, wherein generating recommended content for the target object based on the topic set comprises: constructing a set of topic objects associated with a set of topics in the topic collection; and Based on the attributes of the group of subject objects, recommended content for the target object is generated. The method according to claim 8, wherein the attribute comprises at least one of the following: The text identifier of the subject, The color of the theme, Entities associated with the subject, action clustering information, the action clustering information being generated based on action elements of a plurality of interaction events associated with a topic, knowledge clustering information, the knowledge clustering information being generated based on knowledge elements of a plurality of interaction events associated with a topic, Status information of a topic, indicating the urgency of the topic. The method according to claim 1, wherein the recommended content includes structured content associated with a specific time period, and the structured content is used to describe interaction events within the specific time period. The method according to claim 10, wherein the structured content includes a work summary associated with the specific time period. The method according to claim 1, wherein the recommended content includes message summary content, the message summary content indicating the importance level of a group of messages associated with the target object. The method of claim 12, wherein the group of messages includes unread messages of the target object. The method according to claim 1, wherein the recommended content includes at least one of the following: Overview content associated with a specific entity, To-do content for the target object, The reminder content for the target object. An information processing method, comprising: Acquiring first information associated with the target object; and Based on the first information, recommended content is provided to the target object, wherein the recommended content includes at least one part organized based on at least one theme, each part includes at least one content item associated with the corresponding theme, and the at least one content item is generated based on at least historical interaction information within a preset time period. According to the method according to claim 15, at least one content item is generated based on historical interaction information corresponding to multiple interaction events associated with the target topic, wherein the historical interaction information includes at least knowledge elements and action elements, the knowledge elements are used to describe the business objects associated with the corresponding interaction events, and the action elements are used to describe the event types of the corresponding interaction events. The method of claim 15, wherein the at least one content item associated with the corresponding topic comprises: A first type of content item is used to indicate what the target object has completed regarding the corresponding topic; and/or The second type of content item is used to indicate matters to be completed by the target object regarding the corresponding topic. The method according to claim 17, further comprising: In response to receiving a first operation on a first type of content item, presenting a first interface of a target business component, wherein the first interface is used to display information about historical interaction events between the target object and the target business component, the historical interaction events corresponding to the first type of content item. The method according to claim 17, further comprising: In response to receiving a second operation on a second type of content item, a task associated with the to-do item is created. The method according to claim 15, further comprising: Based on the editing operation of the target object, an identification of the at least one subject is updated, where the identification includes a text identification, a color identification or an image identification. The method according to claim 15, wherein the business object in the at least one content item is displayed in a target style, and the method further comprises: Based on a third operation on the business object, a second interface associated with the business object is presented. The method according to claim 15, wherein providing recommended content to the target object comprises: In a conversation with a digital assistant, the digital assistant provides the recommended content to the target object. The method according to claim 15, further comprising: Based on a fourth operation on the recommended content, a target document is created, where the target document contains at least a portion of the recommended content. The method according to claim 15, wherein the recommended content is a summary of the target object's work during the preset time period. The method according to claim 15, further comprising: In association with the recommended content, presenting a first subscription entry; and Based on the selection of the first subscription entry, recommended content corresponding to a corresponding time period is periodically provided to the target object. The method according to claim 25, further comprising: In association with the recommended content corresponding to the corresponding time period, presenting a first unsubscribe entry; and Based on the selection of the first unsubscribe entry, the provision of recommended content corresponding to the subsequent time period to the target object is stopped. An information processing method, comprising: Acquiring second information associated with the target object; and Based on the second information, recommended content is provided to the target object, wherein the recommended content includes multiple parts corresponding to different message classifications, each part includes a group of content items corresponding to the corresponding message classification, each content item is generated based on a group of unread messages of the target object, and the message classification indicates the importance level of the unread messages corresponding to the group of content items. The method according to claim 27, further comprising: In association with the set of content items, an identification of a conversation corresponding to unread messages associated with the set of content items is presented. The method according to claim 27, further comprising: Based on a fifth operation on the set of content items, a viewing interface of a target conversation is presented, wherein the target conversation corresponds to unread messages associated with the set of content items. The method according to claim 27, further comprising: Based on a sixth operation on the group of content items, unread messages associated with the group of content items are marked as read. The method of claim 27, wherein the importance level of the unread message is determined by processing a set of descriptive information associated with the unread message using a first model. The method of claim 27, wherein the content item is generated by processing at least one unread message having the same importance level using a second model. The method according to claim 27, further comprising: In association with the recommended content, presenting a second subscription entry; and Based on the selection of the second subscription entry, recommended content corresponding to a corresponding time period is periodically provided to the target object. The method according to claim 33, further comprising: In association with the recommended content corresponding to the corresponding time period, presenting a second unsubscribe entry; and Based on the selection of the second unsubscribe entry, the provision of recommended content corresponding to the subsequent time period to the target object is stopped. An apparatus for information processing, comprising: A first acquisition module is configured to acquire historical interaction information of a target object, where the historical interaction information is generated based on a set of interaction events between the target object and at least one business component; A topic determination module, configured to determine a topic set of the group of interaction events based on the historical interaction information; and The content generation module is configured to generate recommended content for the target object based on the topic set. An apparatus for information processing, comprising: A second acquisition module is configured to acquire first information associated with the target object; and A first providing module is configured to provide recommended content to the target object based on the first information, wherein the recommended content includes at least one part organized based on at least one theme, each part includes at least one content item associated with the corresponding theme, and the at least one content item is generated based on at least historical interaction information within a preset time period. An apparatus for information processing, comprising: A third acquisition module is configured to acquire second information associated with the target object; and A second providing module is configured to provide recommended content to the target object based on the second information, wherein the recommended content includes multiple parts corresponding to different message classifications, each part includes a group of content items corresponding to the corresponding message classification, each content item is generated based on a group of unread messages of the target object, and the message classification indicates the importance level of the unread messages corresponding to the group of content items. An electronic device, comprising: at least one processing unit; and At least one memory, the at least one memory being coupled to the at least one processing unit and storing instructions for execution by the at least one processing unit, the instructions, when executed by the at least one processing unit, causing the electronic device to perform a method according to any one of claims 1 to 14, claims 15 to 26, or claims 27 to 34. A computer-readable storage medium having a computer program stored thereon, the computer program being executable by a processor to implement the method according to any one of claims 1 to 14, claims 15 to 26, or claims 27 to 34.