HK1176149A - Automatic application of targeted advertising in datasets - Google Patents

Description

Automated application of targeted advertisements in a data set

Technical Field

The application relates to automated application of targeted advertising in a data set.

Background

Computers have become highly integrated in work, homes, mobile devices, and many other places. Computers can process large amounts of information quickly and efficiently. Software applications designed to run on computer systems allow users to perform a wide variety of functions including business applications, school assignments, entertainment, and the like. Software applications are typically designed to perform specific tasks, such as word processor applications for drafting documents or email programs for sending, receiving and organizing emails.

In some cases, software applications may be designed to access and present data to users. For example, an application may be designed to access a data set and automatically arrange the data into a consistent and organized display. A data set may include a large amount of data that is stored for many years. Providing data to a user may involve bandwidth, servers, and other costs.

Disclosure of Invention

Embodiments described herein relate to providing an advertising model for delivering advertisements and data sets and to streaming data sets that include targeted advertisements. In an embodiment, an instantiated advertising model receives a query for data from a user. The advertising model is communicatively connected to a data store that includes a plurality of data sets. The query requests data from one or more of these data sets. The advertising model determines which data sets are to be retrieved based on the query. The advertising model adds the targeted advertisement to the determined data set and sends the determined data set to the user with the targeted advertisement.

In another embodiment, the instantiated advertising model receives a query for data from a user. The advertising model is communicatively connected to a data store that includes a plurality of data sets. The query requests data from one or more of these data sets. The advertising model determines which data sets are to be retrieved based on the query. The advertising model determines which advertisements to include with the determined data set based on various user-dependent factors and dynamically combines the determined data set and the determined advertisements as data is streamed to the user.

This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.

Additional features and advantages will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the teachings herein. The features and advantages of the invention may be realized and obtained by means of the instruments and combinations particularly pointed out in the appended claims. Features of the present invention will become more fully apparent from the following description and appended claims, or may be learned by the practice of the invention as set forth hereinafter.

Drawings

To further clarify the above and other advantages and features of embodiments of the present invention, a more particular description of embodiments of the present invention will be rendered by reference to the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail through the use of the accompanying drawings in which:

FIG. 1 illustrates a computer architecture in which embodiments of the present invention may operate, including providing an advertising model for delivering advertisements and data sets.

FIG. 2 illustrates a flow diagram of an example method for providing an advertising model for delivering advertisements and data sets.

FIG. 3 illustrates a flow diagram of an example method for streaming a data set including targeted advertisements.

FIG. 4 illustrates an alternative computer architecture for providing an advertising model that delivers advertisements and data sets.

Detailed Description

Embodiments described herein relate to providing an advertising model for delivering advertisements and data sets and to streaming data sets that include targeted advertisements. In an embodiment, an instantiated advertising model receives a query for data from a user. The advertising model is communicatively connected to a data store that includes a plurality of data sets. The query requests data from one or more of these data sets. The advertising model determines which data sets are to be retrieved based on the query. The advertising model adds the targeted advertisement to the determined data set and sends the determined data set to the user with the targeted advertisement.

In another embodiment, the instantiated advertising model receives a query for data from a user. The advertising model is communicatively connected to a data store that includes a plurality of data sets. The query requests data from one or more of these data sets. The advertising model determines which data sets are to be retrieved based on the query. The advertising model determines which advertisements to include with the determined data set based on various user-dependent factors and dynamically combines the determined data set and the determined advertisements as data is streamed to the user.

The following discussion now refers to various methods and method acts that may be performed. It should be noted that while the method acts may be discussed in a certain order or depicted in a flowchart as occurring in a particular order, that particular order is not necessarily required unless specifically stated or otherwise required before one act is performed because the act is dependent on the completion of another act.

Embodiments of the present invention may comprise or utilize a special purpose or general-purpose computer including computer hardware, such as, for example, one or more processors and system memory, as discussed in greater detail below. Embodiments within the scope of the present invention also include physical and other computer-readable media for carrying or storing computer-executable instructions and/or data structures. Such computer-readable media can be any available media that can be accessed by a general purpose or special purpose computer system. Computer-readable media storing computer-executable instructions are computer storage media. Computer-readable media bearing computer-executable instructions are transmission media. Thus, by way of example, and not limitation, embodiments of the invention can include at least two significantly different computer-readable media: computer storage media and transmission media.

Computer storage media includes RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store desired program code means in the form of computer-executable instructions or data structures and which can be accessed by a general purpose or special purpose computer.

A "network" is defined as one or more data links that allow electronic data to be transferred between computer systems and/or modules and/or other electronic devices. When information is transferred or provided over a network or another communications connection (either hardwired, wireless, or a combination of hardwired or wireless) to a computer, the computer properly views the connection as a transmission medium. Transmission media can include a network and/or data links which can be used to carry desired program code means in the form of computer-executable instructions or data structures and which can be accessed by a general purpose or special purpose computer. Combinations of the above should also be included within the scope of computer-readable media.

Further, upon reaching various computer system components, program code means in the form of computer-executable instructions or data structures can be transferred automatically from transmission media to computer storage media (or vice versa). For example, computer-executable instructions or data structures received over a network or a data link may be buffered in RAM within a network interface module (e.g., a "NIC") and then eventually transferred to computer system RAM and/or to less volatile computer storage media at a computer system. Thus, it should be understood that computer storage media can be included in computer system components that also utilize (or even primarily utilize) transmission media.

Computer-executable instructions comprise, for example, instructions and data which cause a general purpose computer, special purpose computer, or special purpose processing device to perform a certain function or group of functions. The computer-executable instructions may be, for example, binaries, intermediate format instructions such as assembly language, or even source code. Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the features and acts described above are disclosed as example forms of implementing the claims.

Those skilled in the art will appreciate that the invention may be practiced in network computing environments with many types of computer system configurations, including, personal computers, desktop computers, laptop computers, message processors, hand-held devices, multi-processor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, mobile telephones, PDAs, pagers, routers, switches, and the like. The invention may also be practiced in distributed system environments (e.g., cloud computing, cloud services, etc.) where local and remote computer systems, which are linked (either by hardwired data links, wireless data links, or by a combination of hardwired and wireless data links) through a network, both perform tasks. In a distributed system environment, program modules may be located in both local and remote memory storage devices.

FIG. 1 illustrates a computer architecture 100 in which the principles of the present invention may be employed. Computer architecture 100 includes an advertising model 110. The advertising model may be instantiated on a single computer system or on multiple computer systems. For example, in some embodiments, an advertising model may be instantiated on the cloud. The advertising model is configured to receive data queries 106 from, for example, users 105. The data query may request data from the data store 130. Data storage may include local or remote storage and may likewise be stored on a single computer system or on multiple computer systems (e.g., on a Storage Area Network (SAN) or on the cloud). The data requested by the user may be part of the data set 131. Each data set may include multiple portions of data 132. In some cases, the data may represent a large portion of the data that was stored for years. This data may be provided to the user along with some form of advertising.

The data set determination module 115 of the advertising model 110 may be configured to receive a user data request and determine from the data store which data set/sets are to be retrieved. The ad targeting module 120 may determine which ad is most relevant to the user based on one or more factors 121, including the type of data requested by the user, metadata information about the requested data, previous usage information associated with the user, contextual information about the context in which the data is to be displayed, and other factors. The advertisement addition module 125 may add the determined advertisements most relevant or appropriate to the user to the retrieved data set. Thus, the determined data set 131D retrieved from the data store and the targeted advertisement 133 added to the data by the advertisement addition module 125 may be sent to the user 105 together.

In some embodiments, the advertising module 110 may be designed to treat the data set as an advertisement inventory. The advertisement inventory may include an advertisement location that identifies where the advertisement is to be placed on the screen. Various techniques may be used to target advertisements for the inventory, and various techniques may be used to present advertisements with the data set 131. Content providers publishing data sets may choose to enable advertising-enabled pricing models and control how advertisements are delivered with their data sets. Such pricing models may include cost per impression, cost per click, and cost per action. In the cost per impression model, a content provider may charge an advertiser for each time an advertisement is viewed or loaded (i.e., impressions) in a web page. In the cost per click model, the content provider may charge the advertiser for each time an advertisement is clicked. In the cost per action model, the content provider may charge the advertiser for each advertisement that is clicked and take an action based on the click. Other pricing models may be used, and the examples provided should not be construed as limiting the types of pricing models that may be used.

Various targeting techniques may be used to determine which advertisements to display with which data. One type of orientation technique may be: and (4) data orientation. In data targeting, the content of the data set retrieved by an application or end user determines which advertisements are displayed. The second targeting technique is metadata targeting. In metadata targeting, information about the data set, content provider, or other non-data information determines which advertisements are displayed. A third targeting technique is behavioral targeting. In behavioral targeting, an application or previous use by an end user across multiple data sets and content providers determines which advertisements are displayed. A fourth targeting technique is context targeting. In contextual targeting, information about the context in which data is displayed determines which advertisements are displayed, including other aspects of the application or website. As will be appreciated by those skilled in the art, other types of orientation techniques may be used in addition to or as an alternative to these listed orientation techniques.

Various different methods for delivering advertisements may be used. Stream (in-stream) delivery advertisements can be delivered as part of a data set (as separate rows or separate columns or both). The end user or application displays the advertisement along with the data. The data and advertisements may be presented by the service. End users or application developers indicate to the service what data they wish to view and the service presents advertisements with the data. This approach allows the service to ensure that the advertisement is in fact displayed rather than being spoofed by the application developer or end user. Additionally or alternatively, the data and advertisements may be presented by the application. The advertisements may be distributed with the data sets to an application in which the application presents the advertisements, possibly differently depending on the application.

Content providers may be presented with various options for how to monetize their data sets using advertisements. The content provider may configure various information such as the bid amount of the advertisement per transaction or per other unit of their data set, restrictions on the types of advertisements that can be displayed with their data, and other settings.

In addition, application developers can use multiple models to select datasets that support advertising (advertising) in their applications. Which models are available to an application developer may depend on the degree of trust the service owner has with the developer, whether the application has been validated, and other factors. In one model for application developers, advertisements are returned as part of the data (either as a separate row or as an additional column). In this model, the application developer processes and displays the additional advertisements as it would any other data.

Another model involves the application developer composing a declarative representation of how data should be displayed to the end user, and possible interactions with that data. The declarative representation may include hints from the developer as to where the advertisement may be displayed in the application (if not, the service may automatically determine this). The service retrieves data and advertisements using the declarative representation and queries from the application as to what data should be displayed and presents the advertisements using the declarative representation, output images, markup, or other representation of the presented application, which is returned to the application or directly to the end user for display.

Another model returns the advertisement with the data, leaving the application to present the advertisement in the appropriate location in the application. Particularly in this model, but also for the other two models above, application developers may be motivated to display advertisements appropriately through the system, where they are compensated for displaying advertisements or other metrics derived therefrom (clicks on advertisements or other downstream actions, such as e-commerce purchases).

In determining what advertisements to display, the advertising model 110 may use various factors. Queries issued by an application or end user 105 may be analyzed to determine which data and advertisements are appropriate for display. Also, metadata about the data being retrieved can be used, such as the title of the data set, various market descriptions, content provider information, and also other data crawled from other systems or web pages and associated with the content provider or data set. In addition, the returned data itself can be analyzed to determine relevant advertisements. For example, a search for a restaurant zip-coded 98101 for a point of interest of a data set may return a restaurant (from the owner of the restaurant) corresponding to the unit of the advertisement listing. In this case, the data itself may be replaced with a stream of advertisements that provide a better image or longer description than would be provided by a normal restaurant entry. The context in which the data is displayed may also be used to target advertisements. This may be a web page on which the data is embedded, profile information about the application developer in the service, or other information.

In some cases, since the user is known, various behavioral techniques can be used to determine the appropriate targeted advertisement. The user's previous actions on the data set 131 of the data store 130 may target which advertisements are displayed. Also, the unique user identity of a service may be correlated with user identities in other services and other advertising platforms, such that advertisements served through the current service are targeted based on user actions in other services or other sites. In some embodiments, any two or more of the above orientation methods may be combined or used together. In this way, targeted advertisements may be combined with the data set and displayed to the user. The concepts described above are described in more detail below with respect to the methods 200 and 300 of fig. 2 and 3.

In view of the above-described systems and architectures, methodologies that may be implemented in accordance with the disclosed subject matter will be better appreciated with reference to the flow charts of fig. 2 and 3. For purposes of simplicity of explanation, the methodologies are shown and described as a series of blocks. It is to be understood and appreciated, however, that the claimed subject matter is not limited by the order of the blocks, as some blocks may occur in different orders and/or concurrently with other blocks from what is depicted and described herein. Moreover, not all illustrated blocks may be required to implement the methodologies described hereinafter.

FIG. 2 illustrates a flow diagram of a method 200 for providing an advertising model for delivering advertisements and data sets. The method 200 will now be described with frequent reference to the components and data of the environment 100.

Method 200 includes an act of receiving a query for data from a user at an instantiated advertising model, wherein the advertising model is communicatively connected to a data store comprising a plurality of data sets, wherein the query is requesting data from one or more of the data sets (act 210). For example, the data set determination module 115 of the advertising model 110 can receive the data query 106 from the user 105. The advertising model may be configured to transmit data to the data store 130 and receive data from the data store 130. The data store stores data sets, each having their own data. A user, software application, or other entity may request substantially any number of data sets from data store 130.

Method 200 includes an act of the advertising model determining which data sets are to be retrieved based on the query (act 220). For example, the data set determination module 115 of the advertising model 110 may determine which data sets 131 to retrieve from the data store based on the received data query 106. The data may be retrieved and temporarily stored at the advertising model so that advertisements may be added to the data set before being sent to the user or application.

Method 200 also includes an act of the advertising model adding one or more targeted advertisements to the determined data set (act 230). For example, ad addition module 120 may add those ads determined by ad targeting module 120 to be most relevant to the data retrieved by module 115. The targeted advertisements may be targeted to a user or application based on one or more user-customizable factors 121. These factors may be selected by the content provider (e.g., the content provider providing the data set 131) or by another user. Each factor may be customizable and may include various settings that may be dynamically adjusted.

In some cases, the user-customizable factors 121 may include the content of the data set, such that advertisements are targeted to the user based on the data of the data set. Thus, in this case, advertisements related to the requested data may be displayed to the user. For example, if a user requests an upcoming sporting event for a particular team, an advertisement (which is included in the data set) relating to the location of the upcoming event may be displayed to the user. In other cases, the user-customizable factors may include metadata information about the data set being retrieved, such that advertisements are targeted to the user based on the metadata information about the data set. For example, the information about the data set may include content provider information, information about the size of the data set, the origin of the data set, the creator of the data, reporting tools that may be used with the data, or other information. Each portion of the metadata information may be used to further target a particular advertisement to a particular user.

In some cases, the user-customizable factors may include user behavior, such that advertisements are targeted to the user based on the user's previous usage data. This usage data can be used to target a particular advertisement to a user if the user has interacted with the advertising model or with a particular set of data in the past. In other cases, the user-customizable factors may include data context, such that advertisements are targeted to the user based on the current context in which the data is displayed. Thus, the advertising model can determine how data is being displayed or is about to be displayed, and can select particular advertisements accordingly.

In some embodiments, advertisers or content providers may elect to promote certain advertisements that are promoted relative to other advertisements. The advertiser may pay a fee to the owner of the data to do so. Advertisements can be promoted in a variety of ways, including increasing the size, placement, color scheme, or other features to make the advertisement stand out relative to other advertisements.

As explained above, targeted advertisements incorporated into the data set charge advertisers a fee in a cost per impression basis. In such a scenario, an advertiser may pay a fee to the content owner or creator each time an advertisement is displayed with the data. In some cases, the data provider or host may act as a middleman (middleman) or agent that facilitates paying for advertisements. In a cost per click scenario, an advertiser will pay the content owner or creator each time an advertisement is clicked on or otherwise selected. In a cost per action scenario, an advertiser will pay the content owner or creator each time an advertisement results in the sale of the goods or services being advertised. Other charging means are also available and the above charging means may be combined with each other as well as with other charging means.

Method 200 includes an act of the advertising model sending the determined data set to the user along with one or more targeted advertisements (act 240). For example, the advertising model 110 can send the determined data set 131D plus the targeted advertisement 133 to a user or application. In some cases, the advertisement is added as a separate data set from the determined data set. Thus, in this case, the data may be separate from the data that is part of the data set and provided in a different row or column. When the data and advertisements are received at the user's computer system or at an application, the application or another service may present the data and advertisements. In the case of a service presenting data and advertisements, the service may ensure to the advertiser that the advertisement is being displayed and is not stripped or blocked. In some cases, a hint may be added to the data set to indicate where the advertisement is to be displayed in the presentation of the service.

FIG. 3 illustrates a flow chart of a method 300 for streaming data sets including targeted advertisements. The method 300 will now be described with frequent reference to the components and data of the environment 400.

Method 300 includes an act of receiving a query for data from a user at an instantiated advertising model, wherein the advertising model is communicatively connected to a data store comprising a plurality of data sets, wherein the query is requesting data from one or more of the data sets (act 310). For example, a user or application (e.g., application B (450B)) may send a data request 453 to the data set distribution module 460. The data set distribution module 460 may be configured to access the data set 480 to provide the requested data.

Method 300 includes an act of the advertising model determining which data sets are to be retrieved based on the query (act 320). For example, data set distribution module 460 may determine which data sets to retrieve based on query 453. Using this determination, the distribution module can retrieve the appropriate data set.

Method 300 includes an act of the advertisement model determining which advertisements to include with the determined data set based on one or more user-customizable factors (act 330). For example, the ad targeting engine 465 may determine which ads from the ad inventory 461 are to be included with the retrieved data set based on factors included in the module 466-469. The data targeting module 466 can be used to target advertisements based on the content of the retrieved data. The metadata targeting module 467 can target advertisements based on metadata information 470 associated with the retrieved data set. The context targeting module 468 can target advertisements based on the context in which the advertisements are to be displayed (e.g., in application a (450A) presented using a service, or in application B (450B) presented using a stream). The behavior targeting module 469 may target advertisements based on a user's or application's previous usage of the retrieved data set or other user data 475.

Method 300 includes an act of the advertising model dynamically combining the determined data set with the determined advertisement while streaming data to the user (act 340). For example, the ad presentation engine 455 may dynamically combine the retrieved data set 480 and the targeted ad and send the combination 452 to the application. In an embodiment, application a may implement service presentation. The application may send a presentation request 451 where the ad presentation engine will send the presented data and ad 452 to the application for display. In another embodiment, application B may send a data request 453 and receive the data and advertisement 454 in the same stream or in a different stream.

In some cases, an advertisement (e.g., from advertisement inventory 461) is combined with the data set 480 as a column of information to be displayed with the data set. In other cases, the advertisement is combined with the data set as a line of information to be displayed with the data set. The user may be able to indicate to the service how the data sets and advertisements are to be presented, and the service may then present the data sets and advertisements according to the user's instructions. The service may provide assurance to the advertiser that the advertisement is being displayed with the data set without being blocked or filtered. Software applications such as A and B (450A and 450B) may present data sets and targeted advertisements according to various software application layout constraints. In this way, the data sets and advertisements may be displayed differently in each software application.

Accordingly, systems, methods, and computer program products are shown that provide an advertising model for delivering targeted advertisements and data sets. Further, systems, methods, and computer program products are provided that stream data sets including targeted advertisements to users and/or applications.

The present invention may be embodied in other specific forms without departing from its spirit or essential characteristics. The described embodiments are to be considered in all respects only as illustrative and not restrictive. The scope of the invention is, therefore, indicated by the appended claims rather than by the foregoing description. All changes which come within the meaning and range of equivalency of the claims are to be embraced within their scope.

Claims (10)

1. In a computer networking environment comprising a plurality of computing systems, at a computer system comprising at least one processor and memory, a computer-implemented method of providing an advertising model for delivering advertisements and data sets, the method comprising:

an act of receiving a query 106 for data from a user 105 at an instantiated advertising model 110, wherein the advertising model is communicatively connected to a data store 130 comprising a plurality of data sets 131, wherein the query is requesting data 132 from one or more of the data sets;

an act of the advertising model 110 determining 115 which data sets 131 to retrieve based on the query;

an act of the advertising model 110 adding 125 one or more targeted 120 advertisements to the determined data set; and

an act of the advertising model 110 sending the determined data set 131D to the user with one or more targeted advertisements 133.

2. The method of claim 1, wherein targeted advertisements are targeted to users based on one or more user-customizable factors.

3. The method of claim 2, wherein at least one of the user-customizable factors includes content of a data set, such that advertisements are targeted to users based on the content of the data set.

4. The method of claim 2, wherein at least one of the user-customizable factors includes metadata information about the data set, such that the advertisement is targeted to the user based on the metadata information about the data set.

5. The method of claim 2, wherein at least one of the user-customizable factors includes user behavior such that advertisements are targeted to the user based on the user's previous usage data.

6. The method of claim 2, wherein at least one of the user-customizable factors includes a data context, such that advertisements are targeted to the user based on a current context in which the data is displayed.

7. A computer program product for implementing a method of streaming data sets including targeted advertisements, the computer program product comprising one or more computer-readable storage media having stored thereon computer-executable instructions that, when executed by one or more processors of a computing system, cause the computing system to perform the method, the method comprising:

an act of receiving a query 106 for data from a user 105 at an instantiated advertising model 110, wherein the advertising model is communicatively connected to a data store 130 comprising a plurality of data sets 131, wherein the query is requesting data 132 from one or more of the data sets;

an act of the advertising model 110 determining 115 which data sets 131 to retrieve based on the query;

an act of the advertisement model 110 determining 120 which advertisements to include with the determined dataset based on one or more user-customizable factors 121; and

the advertising model dynamically combines the determined data set 131D and the determined advertisement 133 while streaming data to the user.

8. The computer program product of claim 7, wherein a user indicates to a service how data sets and advertisements are to be presented, and the service presents data sets and advertisements accordingly.

9. The computer program product of claim 8, wherein the service provides a guarantee to the advertiser that the advertisement is being displayed with the data set.

10. A computer system, comprising:

one or more processors;

a system memory;

one or more computer-readable storage media having stored thereon computer-executable instructions that, when executed by the one or more processors, cause the computing system to perform a method for providing an advertising model for delivering advertisements and data sets, the method comprising:

an act of receiving a query 106 from a user 105 for data 132 at an instantiated advertising model 110, wherein the advertising model is communicatively connected to a data store 130 comprising a plurality of data sets 131, wherein the query is requesting data from one or more of the data sets;

an act of the advertising model 110 determining 115 which data sets 131 to retrieve based on the query;

an act of the advertising model 110 determining 120 which advertisements to add to the determined data set based on one or more of the following factors 121: content of the determined data set, metadata information about the determined data set, previous usage information about the user, and context information about a context in which the data is to be displayed;

an act of the advertising model 110 adding 125 the determined targeted advertisement 133 to the determined data set 131D; and

an act of the advertising model 110 sending the determined data set 131D to the user 105 with one or more targeted advertisements 133.