CN108363655B - User behavior characteristic analysis method and device - Google Patents
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- CN108363655B CN108363655B CN201810142449.XA CN201810142449A CN108363655B CN 108363655 B CN108363655 B CN 108363655B CN 201810142449 A CN201810142449 A CN 201810142449A CN 108363655 B CN108363655 B CN 108363655B
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Abstract
The invention provides a user behavior characteristic analysis method and a device, wherein the method comprises the following steps: acquiring behavior data of a terminal device user; the behavior data includes: a terminal device identifier or a user identifier, an identifier of application software used by a user, a behavior type and behavior content; determining a user behavior identifier according to the terminal equipment identifier or the user identifier and the identifier of the application software; adding the behavior content and the user behavior identification into a queue corresponding to the behavior type; the behavior content is calculated according to the characteristic analysis algorithm corresponding to the behavior type aiming at each queue, the user behavior characteristic corresponding to the behavior content is determined, application software does not need to be provided with a corresponding log real-time acquisition tool, a log real-time transmission tool and a real-time calculation engine, the analysis cost of the user behavior characteristic is reduced, the method can be suitable for application software with different log formats, and the analysis efficiency of the user behavior characteristic is improved.
Description
Technical Field
The invention relates to the technical field of internet, in particular to a user behavior characteristic analysis method and device.
Background
The current app user behavior feature analysis method mainly includes the steps of collecting user behavior logs and transmitting the user behavior logs to a calculation engine, and calculating user behaviors by the calculation engine to obtain user behavior features. However, in the above method for analyzing user behavior characteristics, when a log real-time acquisition tool, a log real-time transmission tool, or a real-time computation engine is absent in the app product technical framework, a new set of technical stack needs to be introduced into the app product technical framework to implement the absent tool, which results in higher learning and operation and maintenance costs, and is difficult to be used for analyzing the app user behavior characteristics in time, thereby reducing the analysis efficiency of the app user behavior characteristics and improving the analysis cost. Different apps and different user behavior log formats are introduced, so that different technical stacks are introduced according to different apps, and the analysis cost is greatly increased.
Disclosure of Invention
The present invention is directed to solving, at least to some extent, one of the technical problems in the related art.
Therefore, a first objective of the present invention is to provide a user behavior feature analysis method, which is used to solve the problems of high analysis cost and poor analysis efficiency in the prior art.
A second object of the present invention is to provide a user behavior feature analysis device.
The third purpose of the invention is to provide another user behavior characteristic analysis device.
A fourth object of the invention is to propose a non-transitory computer-readable storage medium.
A fifth object of the invention is to propose a computer program product.
In order to achieve the above object, an embodiment of a first aspect of the present invention provides a user behavior feature analysis method, including:
acquiring behavior data of a terminal device user; the behavior data includes: a terminal device identifier or a user identifier, an identifier of application software used by a user, a behavior type and behavior content;
determining a user behavior identifier according to the terminal equipment identifier and the identifier of the application software, or according to the user identifier and the identifier of the application software;
adding the behavior content and the user behavior identification into a queue corresponding to the behavior type;
and aiming at each queue, calculating the behavior content according to a characteristic analysis algorithm corresponding to the behavior type, and determining the user behavior characteristics corresponding to the behavior content.
Further, the determining a user behavior identifier according to the terminal device identifier and the identifier of the application software, or according to the user identifier and the identifier of the application software, includes:
performing hash calculation on the terminal equipment identifier and the application software identifier to determine a user behavior identifier; or,
and performing hash calculation on the user identifier and the identifier of the application software to determine a user behavior identifier.
Further, the queue is a circular queue.
Further, the method further comprises the following steps: and storing the user behavior identification and the corresponding user behavior characteristics.
According to the user behavior characteristic analysis method, the behavior data of the terminal equipment user is obtained; the behavior data includes: a terminal device identifier or a user identifier, an identifier of application software used by a user, a behavior type and behavior content; determining a user behavior identifier according to the terminal equipment identifier and the application software identifier, or according to the user identifier and the application software identifier; adding the behavior content and the user behavior identification into a queue corresponding to the behavior type; the behavior content is calculated according to the characteristic analysis algorithm corresponding to the behavior type aiming at each queue, and the user behavior characteristic corresponding to the behavior content is determined, so that the application software does not need to be provided with a corresponding log real-time acquisition tool, a log real-time transmission tool and a real-time calculation engine, and only the application software can report each piece of behavior data of the user in real time, the analysis cost of the user behavior characteristic is reduced, the user behavior characteristic analysis method can be suitable for the application software with different log formats, and the analysis efficiency of the user behavior characteristic is improved.
To achieve the above object, a second aspect of the present invention provides a user behavior feature analysis apparatus, including:
the acquisition module is used for acquiring behavior data of a terminal equipment user; the behavior data includes: a terminal device identifier or a user identifier, an identifier of application software used by a user, a behavior type and behavior content;
the determining module is used for determining a user behavior identifier according to the terminal equipment identifier and the identifier of the application software, or according to the user identifier and the identifier of the application software;
the adding module is used for adding the behavior content and the user behavior identifier into a queue corresponding to the behavior type;
and the computing module is used for computing the behavior content according to a characteristic analysis algorithm corresponding to the behavior type aiming at each queue and determining the user behavior characteristics corresponding to the behavior content.
Further, the determining module is specifically configured to,
performing hash calculation on the terminal equipment identifier and the application software identifier to determine a user behavior identifier; or,
and performing hash calculation on the user identifier and the identifier of the application software to determine a user behavior identifier.
Further, the queue is a circular queue.
Further, the device further comprises:
and the storage module is used for storing the user behavior identification and the corresponding user behavior characteristics.
The user behavior characteristic analysis device of the embodiment of the invention obtains the behavior data of the terminal equipment user; the behavior data includes: a terminal device identifier or a user identifier, an identifier of application software used by a user, a behavior type and behavior content; determining a user behavior identifier according to the terminal equipment identifier and the application software identifier, or according to the user identifier and the application software identifier; adding the behavior content and the user behavior identification into a queue corresponding to the behavior type; the behavior content is calculated according to the characteristic analysis algorithm corresponding to the behavior type aiming at each queue, and the user behavior characteristic corresponding to the behavior content is determined, so that the application software does not need to be provided with a corresponding log real-time acquisition tool, a log real-time transmission tool and a real-time calculation engine, and only the application software can report each piece of behavior data of the user in real time, the analysis cost of the user behavior characteristic is reduced, the user behavior characteristic analysis method can be suitable for the application software with different log formats, and the analysis efficiency of the user behavior characteristic is improved.
In order to achieve the above object, a third embodiment of the present invention provides another user behavior feature analysis device, including: memory, processor and computer program stored on the memory and executable on the processor, characterized in that the processor implements the user behavior feature analysis method as described above when executing the program.
In order to achieve the above object, a fourth aspect of the present invention provides a non-transitory computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the user behavior feature analysis method as described above.
In order to achieve the above object, a fifth aspect of the present invention provides a computer program product, wherein when executed by an instruction processor in the computer program product, a user behavior feature analysis method is performed, and the method includes:
acquiring behavior data of a terminal device user; the behavior data includes: a terminal device identifier or a user identifier, an identifier of application software used by a user, a behavior type and behavior content;
determining a user behavior identifier according to the terminal equipment identifier and the identifier of the application software, or according to the user identifier and the identifier of the application software;
adding the behavior content and the user behavior identification into a queue corresponding to the behavior type;
and aiming at each queue, calculating the behavior content according to a characteristic analysis algorithm corresponding to the behavior type, and determining the user behavior characteristics corresponding to the behavior content.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
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The foregoing and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a schematic flow chart of a user behavior feature analysis method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a user behavior feature analysis apparatus according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of another user behavior feature analysis apparatus according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
The following describes a user behavior feature analysis method and apparatus according to an embodiment of the present invention with reference to the drawings.
Fig. 1 is a schematic flow chart of a user behavior feature analysis method according to an embodiment of the present invention. As shown in fig. 1, the user behavior feature analysis method includes the following steps:
s101, acquiring behavior data of a terminal device user; the behavior data includes: a terminal device identification or a user identification, an identification of application software used by the user, a behavior type and a behavior content.
The execution main body of the user behavior characteristic analysis method provided by the invention is a user behavior characteristic analysis device, and the user behavior characteristic analysis device can be hardware equipment which is communicated with the terminal equipment, such as a background server and a server cluster which correspond to the terminal equipment, or software installed on the hardware equipment.
In this embodiment, the behavior data may be an operation behavior of the user when using each application software on the terminal device. Application software such as WeChat, QQ, Paibao, etc. The identifier of the application software is an identifier that uniquely identifies the application software, such as the name or number of the application software. The terminal device identifier may be, for example, a Called User Identification number (CUID) of the terminal device, or a Media Access Control address (MAC) of the terminal device.
In this embodiment, the user identifier may be an identifier of a user who logs in the application software, and may be, for example, personal information such as a login account number or a name of the user who logs in the application software. The behavior type can be the operation type of the application software by the user, such as page turning, inputting, backspacing, deleting, paying attention off and the like. The action content may be, for example, input content, deleted content, an object of interest, an object of canceling interest, or the like.
In this embodiment, the terminal device that installs the application software may obtain the current behavior data of the user in real time and report the current behavior data of the user in real time when the user uses the application software, so that the user behavior feature analysis device may analyze the current behavior data without acquiring and reporting a behavior log by the terminal device that installs the application software, thereby reducing the amount of data transmitted by the terminal device, expanding the application range of the user behavior feature analysis method, and improving the analysis efficiency of the user behavior feature.
Further, in this embodiment, the process of the terminal device acquiring the current behavior data of the user may specifically be acquiring an identifier of application software used by the terminal device user, a behavior type of the user, and behavior content; judging whether the application software is in a login state; and when the application software is in an unregistered state, acquiring a terminal equipment identifier, and reporting behavior data comprising the terminal equipment identifier, the identifier of the application software, the behavior type and the behavior content to a user behavior characteristic analysis device. It should be noted that, in this embodiment, a simple interface may be provided on the application software, so that the terminal device can call up the latest behavior data in real time through the interface.
In addition, when the application software is in a login state, the behavior data comprising the login user identification, the application software identification, the behavior type and the behavior content is reported to the user behavior characteristic analysis device.
It should be noted that the terminal device may interact with a background server corresponding to the application software, acquire a login state of the application software, and acquire a user identifier of the login application software when the application software is in the login state.
S102, determining a user behavior identifier according to the terminal equipment identifier and the application software identifier, or according to the user identifier and the application software identifier.
In this embodiment, the terminal device identifier, the application software identifier, and a single identifier in the user identifier may not identify the usage behavior of the specific application software by the specific user, and therefore, in order to identify the usage behavior of the specific application software by the specific user, hash calculation may be performed on the terminal device identifier and the application software identifier, or hash calculation may be performed on the user identifier and the application software identifier, so as to obtain an identifier capable of uniquely identifying the usage behavior of the specific application software by the specific user.
S103, adding the behavior content and the user behavior identification into a queue corresponding to the behavior type.
In this embodiment, queues corresponding to a plurality of behavior types may be set for a single application software; or the queues corresponding to the multiple behavior types are used for analyzing the user behavior characteristics of multiple application software. The queue corresponding to the behavior type may be a linear queue or a circular queue. In the circular queue, a tail pointer overtakes a head pointer forwards during enqueuing; when dequeuing, the head pointer drives the tail pointer forward, so that the head pointer and the tail pointer are equal when the dequeue is empty and the queue is full. The use of the circular queue can avoid locking operation and further improve the processing speed compared with a linear queue.
And S104, calculating the behavior content according to a characteristic analysis algorithm corresponding to the behavior type aiming at each queue, and determining the user behavior characteristics corresponding to the behavior content.
In this embodiment, for each queue, one thread may be called to process the behavior content in the queue, so as to implement parallel processing on each queue and improve the processing speed. In addition, behavior contents of the same behavior type are placed in the same queue, so that the behavior contents of the same behavior type can be processed in a centralized manner by threads, namely the behavior contents of the same behavior type are processed by the same algorithm, the behavior contents of different behavior types are prevented from being processed by calling different algorithms, the streamlined processing is realized, and the processing speed is increased.
In addition, in this embodiment, in the case that the user behavior feature analysis device is a server cluster, the user behavior feature analysis device may set queues corresponding to multiple behavior types on multiple servers of the server cluster, and each server processes behavior data of at least one user, that is, send behavior content and a user behavior identifier of the same user to the same server, so that the server distributes the behavior content and the user behavior identifier of the same user to each queue on the server according to the behavior type for processing, thereby increasing processing speed, facilitating acquisition of multiple user behavior features of the same user, and providing personalized recommendation information, such as recommended application software, to the user according to the multiple user behavior features of the same user.
Further, on the basis of the foregoing embodiment, after step 104, the method may further include: and storing the user behavior identification and the corresponding user behavior characteristics so as to perform personalized recommendation on the user based on each user behavior characteristic of the user in the following.
According to the user behavior characteristic analysis method, the behavior data of the terminal equipment user is obtained; the behavior data includes: a terminal device identifier or a user identifier, an identifier of application software used by a user, a behavior type and behavior content; determining a user behavior identifier according to the terminal equipment identifier and the application software identifier, or according to the user identifier and the application software identifier; adding the behavior content and the user behavior identification into a queue corresponding to the behavior type; the behavior content is calculated according to the characteristic analysis algorithm corresponding to the behavior type aiming at each queue, and the user behavior characteristic corresponding to the behavior content is determined, so that the application software does not need to be provided with a corresponding log real-time acquisition tool, a log real-time transmission tool and a real-time calculation engine, and only the application software can report each piece of behavior data of the user in real time, the analysis cost of the user behavior characteristic is reduced, the user behavior characteristic analysis method can be suitable for the application software with different log formats, and the analysis efficiency of the user behavior characteristic is improved.
Fig. 2 is a schematic structural diagram of a user behavior feature analysis apparatus according to an embodiment of the present invention. As shown in fig. 2, includes: an acquisition module 21, a determination module 22, an addition module 23 and a calculation module 24.
The acquiring module 21 is configured to acquire behavior data of a terminal device user; the behavior data includes: a terminal device identifier or a user identifier, an identifier of application software used by a user, a behavior type and behavior content;
a determining module 22, configured to determine a user behavior identifier according to the terminal device identifier and the identifier of the application software, or according to the user identifier and the identifier of the application software;
an adding module 23, configured to add the behavior content and the user behavior identifier to a queue corresponding to the behavior type;
and the calculating module 24 is configured to calculate the behavior content according to a feature analysis algorithm corresponding to the behavior type for each queue, and determine a user behavior feature corresponding to the behavior content.
The user behavior feature analysis device provided by the invention can be hardware equipment which communicates with the terminal equipment, such as a background server and a server cluster corresponding to the terminal equipment, or software installed on the hardware equipment.
In this embodiment, the behavior data may be an operation behavior of the user when using each application software on the terminal device. Application software such as WeChat, QQ, Paibao, etc. The identifier of the application software is an identifier that uniquely identifies the application software, such as the name or number of the application software. The terminal device identifier may be, for example, a Called User Identification number (CUID) of the terminal device, or a Media Access Control address (MAC) of the terminal device.
In this embodiment, the user identifier may be an identifier of a user who logs in the application software, and may be, for example, personal information such as a login account number or a name of the user who logs in the application software. The behavior type can be the operation type of the application software by the user, such as page turning, inputting, backspacing, deleting, paying attention off and the like. The action content may be, for example, input content, deleted content, an object of interest, an object of canceling interest, or the like.
In this embodiment, the terminal device that installs the application software may obtain the current behavior data of the user in real time and report the current behavior data of the user in real time when the user uses the application software, so that the user behavior feature analysis device may analyze the current behavior data without acquiring and reporting a behavior log by the terminal device that installs the application software, thereby reducing the amount of data transmitted by the terminal device, expanding the application range of the user behavior feature analysis method, and improving the analysis efficiency of the user behavior feature.
Further, in this embodiment, the process of the terminal device acquiring the current behavior data of the user may specifically be acquiring an identifier of application software used by the terminal device user, a behavior type of the user, and behavior content; judging whether the application software is in a login state; and when the application software is in an unregistered state, acquiring a terminal equipment identifier, and reporting behavior data comprising the terminal equipment identifier, the identifier of the application software, the behavior type and the behavior content to a user behavior characteristic analysis device. It should be noted that, in this embodiment, a simple interface may be provided on the application software, so that the terminal device can call up the latest behavior data in real time through the interface.
In addition, when the application software is in a login state, the behavior data comprising the login user identification, the application software identification, the behavior type and the behavior content is reported to the user behavior characteristic analysis device.
In this embodiment, the terminal device identifier, the application software identifier, and a single identifier in the user identifier may not identify the usage behavior of the specific user on the specific application software, and therefore, in order to identify the usage behavior of the specific user on the specific application software, the determining module 22 may be specifically configured to perform hash calculation on the terminal device identifier and the application software identifier to determine the user behavior identifier; or, performing hash calculation on the user identifier and the identifier of the application software to determine the user behavior identifier.
In this embodiment, queues corresponding to a plurality of behavior types may be set for a single application software; or the queues corresponding to the multiple behavior types are used for analyzing the user behavior characteristics of multiple application software. The queue corresponding to the behavior type may be a linear queue or a circular queue. In the circular queue, a tail pointer overtakes a head pointer forwards during enqueuing; when dequeuing, the head pointer drives the tail pointer forward, so that the head pointer and the tail pointer are equal when the dequeue is empty and the queue is full. The use of the circular queue can avoid locking operation and further improve the processing speed compared with a linear queue.
In this embodiment, for each queue, one thread may be called to process the behavior content in the queue, so as to implement parallel processing on each queue and improve the processing speed. In addition, behavior contents of the same behavior type are placed in the same queue, so that the behavior contents of the same behavior type can be processed in a centralized manner by threads, namely the behavior contents of the same behavior type are processed by the same algorithm, the behavior contents of different behavior types are prevented from being processed by calling different algorithms, the streamlined processing is realized, and the processing speed is increased.
In addition, in this embodiment, in the case that the user behavior feature analysis device is a server cluster, the user behavior feature analysis device may set queues corresponding to multiple behavior types on multiple servers of the server cluster, and each server processes behavior data of at least one user, that is, send behavior content and a user behavior identifier of the same user to the same server, so that the server distributes the behavior content and the user behavior identifier of the same user to each queue on the server according to the behavior type for processing, thereby increasing processing speed, facilitating acquisition of multiple user behavior features of the same user, and providing personalized recommendation information, such as recommended application software, to the user according to the multiple user behavior features of the same user.
Further, on the basis of the above embodiment, the apparatus may further include: and the storage module is used for storing the user behavior identification and the corresponding user behavior characteristics so as to perform personalized recommendation on the user based on each user behavior characteristic of the user.
The user behavior characteristic analysis device of the embodiment of the invention obtains the behavior data of the terminal equipment user; the behavior data includes: a terminal device identifier or a user identifier, an identifier of application software used by a user, a behavior type and behavior content; determining a user behavior identifier according to the terminal equipment identifier and the application software identifier, or according to the user identifier and the application software identifier; adding the behavior content and the user behavior identification into a queue corresponding to the behavior type; the behavior content is calculated according to the characteristic analysis algorithm corresponding to the behavior type aiming at each queue, and the user behavior characteristic corresponding to the behavior content is determined, so that the application software does not need to be provided with a corresponding log real-time acquisition tool, a log real-time transmission tool and a real-time calculation engine, and only the application software can report each piece of behavior data of the user in real time, the analysis cost of the user behavior characteristic is reduced, the user behavior characteristic analysis method can be suitable for the application software with different log formats, and the analysis efficiency of the user behavior characteristic is improved.
Fig. 3 is a schematic structural diagram of another user behavior feature analysis apparatus according to an embodiment of the present invention. The user behavior feature analysis device includes:
The processor 1002, when executing the program, implements the user behavior feature analysis method provided in the above-described embodiment.
Further, the user behavior feature analysis device further includes:
a communication interface 1003 for communicating between the memory 1001 and the processor 1002.
A memory 1001 for storing computer programs that may be run on the processor 1002.
The processor 1002 is configured to implement the user behavior feature analysis method according to the foregoing embodiment when executing the program.
If the memory 1001, the processor 1002, and the communication interface 1003 are implemented independently, the communication interface 1003, the memory 1001, and the processor 1002 may be connected to each other through a bus and perform communication with each other. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 3, but this does not mean only one bus or one type of bus.
Optionally, in a specific implementation, if the memory 1001, the processor 1002, and the communication interface 1003 are integrated on one chip, the memory 1001, the processor 1002, and the communication interface 1003 may complete communication with each other through an internal interface.
The processor 1002 may be a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement embodiments of the present invention.
The present invention also provides a non-transitory computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a user behavior feature analysis method as described above.
The present invention also provides a computer program product, which when executed by an instruction processor performs a method of user behavior feature analysis, the method comprising:
acquiring behavior data of a terminal device user; the behavior data includes: a terminal device identifier or a user identifier, an identifier of application software used by a user, a behavior type and behavior content;
determining a user behavior identifier according to the terminal equipment identifier and the identifier of the application software, or according to the user identifier and the identifier of the application software;
adding the behavior content and the user behavior identification into a queue corresponding to the behavior type;
and aiming at each queue, calculating the behavior content according to a characteristic analysis algorithm corresponding to the behavior type, and determining the user behavior characteristics corresponding to the behavior content.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present invention may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (10)
1. A user behavior feature analysis method is characterized by comprising the following steps:
acquiring behavior data of a terminal device user; the behavior data includes: a terminal device identifier or a user identifier, an identifier of application software used by a user, a behavior type and behavior content;
determining a user behavior identifier according to the terminal equipment identifier and the identifier of the application software, or according to the user identifier and the identifier of the application software;
adding the behavior content and the user behavior identification into a queue corresponding to the behavior type;
and aiming at each queue, calculating the behavior content according to a characteristic analysis algorithm corresponding to the behavior type, and determining the user behavior characteristics corresponding to the behavior content.
2. The method of claim 1, wherein the determining the user behavior identifier according to the terminal device identifier and the application software identifier or according to the user identifier and the application software identifier comprises:
performing hash calculation on the terminal equipment identifier and the application software identifier to determine a user behavior identifier; or,
and performing hash calculation on the user identifier and the identifier of the application software to determine a user behavior identifier.
3. The method of claim 1, wherein the queue is a circular queue.
4. The method of claim 1, further comprising:
and storing the user behavior identification and the corresponding user behavior characteristics.
5. A user behavior feature analysis device, comprising:
the acquisition module is used for acquiring behavior data of a terminal equipment user; the behavior data includes: a terminal device identifier or a user identifier, an identifier of application software used by a user, a behavior type and behavior content;
the determining module is used for determining a user behavior identifier according to the terminal equipment identifier and the identifier of the application software, or according to the user identifier and the identifier of the application software;
the adding module is used for adding the behavior content and the user behavior identifier into a queue corresponding to the behavior type;
and the computing module is used for computing the behavior content according to a characteristic analysis algorithm corresponding to the behavior type aiming at each queue and determining the user behavior characteristics corresponding to the behavior content.
6. The apparatus of claim 5, wherein the means for determining is specifically configured to,
performing hash calculation on the terminal equipment identifier and the application software identifier to determine a user behavior identifier; or,
and performing hash calculation on the user identifier and the identifier of the application software to determine a user behavior identifier.
7. The apparatus of claim 5, wherein the queue is a circular queue.
8. The apparatus of claim 5, further comprising:
and the storage module is used for storing the user behavior identification and the corresponding user behavior characteristics.
9. A user behavior feature analysis device, comprising:
memory, processor and computer program stored on the memory and executable on the processor, characterized in that the processor implements the user behavior feature analysis method according to any of claims 1-4 when executing the program.
10. A non-transitory computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the user behavior feature analysis method according to any one of claims 1 to 4.
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| CN113822687B (en) * | 2020-06-19 | 2024-10-29 | 阿里巴巴集团控股有限公司 | Data processing method, device, equipment and storage medium |
| CN113781088A (en) * | 2021-02-04 | 2021-12-10 | 北京沃东天骏信息技术有限公司 | A user tag processing method, device and system |
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