CN113362097A - User determination method and device - Google Patents
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Abstract
The invention discloses a user determination method and device, and relates to the technical field of computers. One embodiment of the method comprises: acquiring a user portrait of a registered user; acquiring behavior path data of a registered user; comparing the user portrait of the registered user with the behavior path data by using a historical behavior path data set to determine a target user, wherein the historical behavior path data set indicates the application service completion probability corresponding to the historical behavior path data, and the target user refers to the registered user meeting the application service completion probability threshold. The implementation mode reduces the workload of user determination and improves the accuracy of the determined target user.
Description
Technical Field
The present invention relates to the field of computer technologies, and in particular, to a user determination method and apparatus.
Background
With the development of internet technology, more and more companies begin to develop corresponding application services on line. In order to expand the business of each company, a common and effective means is to put corresponding marketing means for potential users.
In the process of implementing the invention, the inventor finds that at least the following problems exist in the prior art:
in the prior art, the target client is determined only through a single behavior of the user when accessing the application, the workload of the user determination method is large, and the accuracy of the determined target user is low.
Disclosure of Invention
In view of this, embodiments of the present invention provide a user determination method and apparatus, which can reduce workload of user determination and improve accuracy of a determined target user.
To achieve the above object, according to a first aspect of the embodiments of the present invention, there is provided a user determination method, including:
acquiring a user portrait of a registered user;
acquiring behavior path data of a registered user;
comparing the user portrait of the registered user with the behavior path data by using a historical behavior path data set to determine a target user, wherein the historical behavior path data set indicates the application service completion probability corresponding to the historical behavior path data, and the target user refers to the registered user meeting the application service completion probability threshold.
Further, the step of acquiring the behavior path data of the registered user comprises: and determining behavior path data of the registered user for accessing the application once according to the time threshold and the time stamp of each click behavior when the registered user accesses the application, and acquiring the behavior path data.
Further, before the step of comparing the user profile and the behavior path data of the registered user with the historical behavior path data set, the user determination method further includes:
acquiring a user portrait of a historical user;
determining historical behavior path data corresponding to a historical user, wherein the historical behavior path data indicates the completion probability of the application service of the historical user;
a historical behavior path data set is constructed based on the user representation of the historical user and the historical behavior path data.
Further, the historical behavior path data includes first historical behavior path data, and the step of determining the historical behavior path data corresponding to the historical user includes: and determining first historical behavior path data according to historical clicking behaviors of historical users, corresponding timestamps of the historical clicking behaviors and application service completion probability thresholds, wherein the number of the first historical behavior path data is at least one.
Further, the historical behavior path data further includes second historical behavior path data and third historical behavior path data, and the step of determining the historical behavior path data corresponding to the historical user further includes: determining second historical behavior path data according to the association rule; and determining third history behavior path data according to the due business rules.
Further, the user representation includes user attribute information and user behavior information.
Further, the user determination method further includes: and updating the historical behavior path data set according to the behavior path data of the registered user and the application service completion probability of the registered user.
According to a second aspect of the embodiments of the present invention, there is provided a user determination apparatus, including:
the target user determining module is used for acquiring a user portrait of a registered user;
the behavior path data acquisition module is used for acquiring the behavior path data of the registered user;
and the target user determining module is used for comparing the user portrait of the registered user with the behavior path data by utilizing the historical behavior path data set to determine the target user, wherein the historical behavior path data set indicates the application service completion probability corresponding to the historical behavior path data, and the target user refers to the registered user meeting the application service completion probability threshold.
According to a third aspect of embodiments of the present invention, there is provided an electronic apparatus, including:
one or more processors;
a storage device for storing one or more programs,
when executed by one or more processors, cause the one or more processors to implement any of the user determination methods described above.
According to a fourth aspect of embodiments of the present invention, there is provided a computer-readable medium, on which a computer program is stored, which program, when executed by a processor, implements any of the user determination methods described above.
One embodiment of the above invention has the following advantages or benefits: because the user portrait of the registered user is obtained; acquiring behavior path data of a registered user; the user portrait of the registered user and the behavior path data are compared by utilizing the historical behavior path data set to determine the target user, wherein the historical behavior path data set indicates the application service completion probability corresponding to the historical behavior path data, and the target user refers to the technical means of the registered user meeting the threshold of the application service completion probability, so that the technical problems that in the prior art, the target client is determined only through a single behavior when the user accesses the application, the workload of a user determination method is large, and the accuracy of the determined target user is low are solved, the workload of user determination is reduced, and the accuracy of the determined target user is improved.
Further effects of the above-mentioned non-conventional alternatives will be described below in connection with the embodiments.
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The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:
fig. 1 is a schematic diagram of a main flow of a user determination method provided according to a first embodiment of the present invention;
fig. 2 is a schematic diagram of a main flow of a user determination method provided according to a second embodiment of the present invention;
FIG. 3 is a schematic diagram of the main modules of a user determination device according to an embodiment of the invention;
FIG. 4 is an exemplary system architecture diagram in which embodiments of the present invention may be employed;
fig. 5 is a schematic block diagram of a computer system suitable for use in implementing a terminal device or server of an embodiment of the invention.
Detailed Description
Exemplary embodiments of the present invention are described below with reference to the accompanying drawings, in which various details of embodiments of the invention are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
Fig. 1 is a schematic diagram of a main flow of a user determination method provided according to a first embodiment of the present invention; as shown in fig. 1, the user determination method provided in the embodiment of the present invention mainly includes:
step S101, obtaining a user portrait of a registered user.
Specifically, according to the embodiment of the present invention, the user representation includes user attribute information and user behavior information.
Wherein the user attribute information includes: basic attribute information such as age, gender, occupation, and user number of the user. The user behavior information includes information such as individual behavior (click behavior) when the user accesses the application, frequency of the click behavior, access times, and time stamps corresponding to the respective click behaviors.
Registering a user: the user who completes registration in the application program but does not execute the corresponding application service, for example, the user who completes registration in a mail application program but does not execute the mail service.
Step S102, behavior path data of the registered user is obtained.
Further, according to an embodiment of the present invention, the step of acquiring the behavior path data of the registered user includes: and determining behavior path data of the registered user for accessing the application once according to the time threshold and the time stamp of each click behavior when the registered user accesses the application, and acquiring the behavior path data.
In a complete behavior path data, a user may briefly quit the application due to other factors (network delay, checking other application information, and the like) during the process of accessing the application to perform a corresponding click behavior operation, in order to obtain a relatively complete behavior path data, by setting a time threshold, after a registered user accesses the application, the click behaviors of the user are sorted according to a timestamp corresponding to each click behavior of the registered user, if a time interval between the current user behavior and the last user behavior is greater than the time threshold, the current access is considered to be finished, and the currently obtained user behavior sorting is determined as the behavior path data corresponding to the current access.
And step S103, comparing the user portrait of the registered user with the behavior path data by using a historical behavior path data set to determine a target user, wherein the historical behavior path data set indicates the application service completion probability corresponding to the historical behavior path data, and the target user refers to the registered user meeting the application service completion probability threshold.
Specifically, according to the user portrait of the registered user and the behavior path data, the user portrait corresponding to the historical user and the historical behavior path data are compared in the historical behavior path data set to determine the target user. According to a specific implementation manner of the embodiment of the invention, the comparison probability can be obtained through comparison, and if the comparison probability is greater than the probability threshold, the registered user is determined to be the target user; and if the comparison probability is smaller than the probability threshold, determining that the registered user is not the target user.
Specifically, according to the embodiment of the present invention, before the step of comparing the user portrait of the registered user with the behavior path data by using the historical behavior path data set, the user determination method further includes:
acquiring a user portrait of a historical user;
determining historical behavior path data corresponding to a historical user, wherein the historical behavior path data indicates the completion probability of the application service of the historical user;
a historical behavior path data set is constructed based on the user representation of the historical user and the historical behavior path data.
History users: the users who have completed registration in the application program include users who do not execute the application service and users who have executed the application service. I.e. the historical users comprise registered users.
The historical behavior path data set is constructed through historical data (namely user figures of historical users and behavior path data of the historical users), and the accuracy of the determined target users is obviously improved.
According to an embodiment of the present invention, the historical behavior path data includes first historical behavior path data, and the step of determining the historical behavior path data corresponding to the historical user includes: and determining first historical behavior path data according to historical clicking behaviors of historical users, corresponding timestamps of the historical clicking behaviors and application service completion probability thresholds, wherein the number of the first historical behavior path data is at least one.
The data used to construct the historical behavior path dataset may include multiple types. The first historical behavior path data is simple and direct to obtain, a plurality of historical behavior path data can be directly determined according to the historical behavior data of the historical user and the time stamps corresponding to the historical behaviors, and then the first historical behavior path data is determined from the plurality of historical behavior path data according to the application service completion threshold. According to a specific implementation manner of the embodiment of the present invention, several pieces of historical behavior path data (a specific determination process may adopt a statistical analysis manner) with a high application service completion degree may be determined as the first historical behavior path data.
Further, according to an embodiment of the present invention, the historical behavior path data further includes second historical behavior path data and third historical behavior path data, and the step of determining the historical behavior path data corresponding to the historical user further includes: determining second historical behavior path data according to the association rule; and determining third history behavior path data according to the due business rules.
Specifically, the first historical behavior path data is determined primarily by means of statistical analysis of the historical data (i.e., based on an application traffic completion threshold). However, the historical behavior path data determined only in the above manner has the disadvantages of long behavior path and no representativeness. In order to further improve the optimization degree of the constructed historical behavior path data set, the accuracy of the determined target user is improved. And identifying two click behaviors which are influential and strongly associated with each other through the association rule, and determining the two click behaviors which meet the conditions as second historical behavior path data.
Meanwhile, third history behavior path data can be determined according to key behaviors given by the target business behaviors according to the time stamp sequence.
Association rules: in the process of accessing the application, if influence and strong correlation exist between two clicking behaviors, even if the two behaviors do not occur closely, the behavior path data can be determined according to the time stamp sequence corresponding to the two behaviors.
And (3) application business behavior: refers to the click behavior that a user must (inevitably) perform when completing the application service of its registered application.
According to the embodiment of the present invention, the user determination method further includes: and updating the historical behavior path data set according to the behavior path data of the registered user and the application service completion probability of the registered user.
According to a specific implementation manner of the embodiment of the present invention, in a case that the operation historical behavior path data set is a historical behavior path model, after the historical behavior path model is constructed, the historical behavior path model may be retrained again according to corresponding data (mainly referring to a user portrait, behavior path data, and application service completion) of a registered user compared by a determined target user, so as to optimize the historical behavior path model and improve accuracy of the determined target user.
According to the technical scheme of the embodiment of the invention, the user portrait of the registered user is obtained; acquiring behavior path data of a registered user; the user portrait of the registered user and the behavior path data are compared by utilizing the historical behavior path data set to determine the target user, wherein the historical behavior path data set indicates the application service completion probability corresponding to the historical behavior path data, and the target user refers to the technical means of the registered user meeting the threshold of the application service completion probability, so that the technical problems that in the prior art, the target client is determined only through a single behavior when the user accesses the application, the workload of a user determination method is large, and the accuracy of the determined target user is low are solved, the workload of user determination is reduced, and the accuracy of the determined target user is improved.
Fig. 2 is a schematic diagram of a main flow of a user determination method provided according to a second embodiment of the present invention; the Application scenario of the present invention may be each Application program, and the Application scenario of this embodiment is an express (mail) app (Application). As shown in fig. 2, the user determining method provided in the embodiment of the present invention mainly includes:
in step S201, a user profile of a historical user is obtained.
Specifically, according to the embodiment of the present invention, the user representation includes user attribute information and user behavior information.
Wherein the user attribute information includes: basic attribute information such as age, gender, occupation, and user number of the user. The user behavior information includes information such as individual behavior (click behavior) when the user accesses the application, frequency of the click behavior, access times, and time stamps corresponding to the respective click behaviors.
History users: the users who have completed registration in the application program include users who do not execute the application service and users who have executed the application service. I.e. the historical users comprise registered users.
Step S202, determining the behavior path data of the historical user, wherein the historical behavior path data indicates the application service completion probability of the historical user.
Further, according to an embodiment of the present invention, the step of acquiring the behavior path data of the application user includes: and determining behavior path data of the registered user for accessing the application once according to the time threshold and the time stamp of each click behavior when the registered user accesses the application, and acquiring the behavior path data.
In a complete behavior path data, a user may briefly quit the application due to other factors (network delay, checking other application information, and the like) during the process of accessing the application to perform a corresponding click behavior operation, in order to obtain a relatively complete behavior path data, by setting a time threshold, after a registered user accesses the application, the click behaviors of the user are sorted according to a timestamp corresponding to each click behavior of the registered user, if a time interval between the current user behavior and the last user behavior is greater than the time threshold, the current access is considered to be finished, and the currently obtained user behavior sorting is determined as the behavior path data corresponding to the current access.
Step S203, a historical behavior path data set is constructed based on the user portrait of the historical user and the historical behavior path data.
The historical behavior path data set is constructed through historical data (namely user figures of historical users and historical behavior path data of the historical users), and the accuracy of the determined target users is obviously improved.
According to an embodiment of the present invention, the historical behavior path data includes first historical behavior path data, and the step of determining the historical behavior path data corresponding to the historical user includes: and determining first historical behavior path data according to historical clicking behaviors of historical users, corresponding timestamps of the historical clicking behaviors and application service completion probability thresholds, wherein the number of the first historical behavior path data is at least one.
The data used to construct the historical behavior path dataset may include multiple types. The first historical behavior path data is simple and direct to obtain, a plurality of historical behavior path data can be directly determined according to the historical behavior data of the historical user and the time stamps corresponding to the historical behaviors, and then the first historical behavior path data is determined from the plurality of historical behavior path data according to the application service completion threshold. According to a specific implementation manner of the embodiment of the present invention, several pieces of historical behavior path data (a specific determination process may adopt a statistical analysis manner) with a high application service completion degree may be determined as the first historical behavior path data.
Further, according to an embodiment of the present invention, the historical behavior path data further includes second historical behavior path data and third historical behavior path data, and the step of determining the historical behavior path data corresponding to the historical user further includes: determining second historical behavior path data according to the association rule; and determining third history behavior path data according to the due business rules.
Specifically, the first historical behavior path data is determined primarily by means of statistical analysis of the historical data (i.e., based on an application traffic completion threshold). However, the historical behavior path data determined only in the above manner has the disadvantages of long behavior path and no representativeness. In order to further improve the optimization degree of the constructed historical behavior path data set, the accuracy of the determined target user is improved. And identifying two click behaviors which are influential and strongly associated with each other through the association rule, and determining the two click behaviors which meet the conditions as second historical behavior path data.
Meanwhile, third history behavior path data can be determined according to key behaviors given by the target business behaviors according to the time stamp sequence.
Association rules: in the process of accessing the application, if influence and strong correlation exist between two clicking behaviors, even if the two behaviors do not occur closely, the behavior path data can be determined according to the time stamp sequence corresponding to the two behaviors.
And (3) application business behavior: refers to the click behavior that a user must (inevitably) perform when completing the application service of its registered application.
According to the embodiment of the present invention, the step of constructing the historical behavior path data set may also be to construct a historical behavior path model, specifically, a logistic regression and xgboost algorithm (extreme gradient lifting algorithm) may be adopted to construct the historical behavior path model, or an existing model construction method may also be adopted to construct the historical behavior path model.
According to a specific implementation manner of the embodiment of the present invention, a user image of an application user, first historical behavior path data, second historical behavior path data, and third historical behavior path data (where the historical behavior path data is binary variables, that is, each historical behavior path data variable corresponds to two values, 0 and 1, respectively, where 1 represents a behavior path indicated by the historical behavior path data that is executed when an application service is completed, and 0 represents a behavior path indicated by the historical behavior path data that is not executed when the application service is completed) are used as arguments, so as to construct a historical behavior path model.
Step S204, obtaining the user portrait of the registered user.
Registering a user: the user who completes registration in the application program but does not execute the application service, for example, the user who completes registration in a mail application program but does not execute the mail service.
In step S205, behavior path data of the registered user is acquired.
Step S206, comparing the user portrait of the registered user with the behavior path data by using a historical behavior path data set to determine a target user, wherein the historical behavior path data set indicates the application service completion probability corresponding to the historical behavior path data, and the target user refers to the registered user meeting the application service completion probability threshold.
Specifically, according to the user portrait of the registered user and the behavior path data, the user portrait corresponding to the historical user and the historical behavior path data are compared in the historical behavior path data set to determine the target user. According to a specific implementation manner of the embodiment of the invention, the comparison probability can be obtained through comparison, and if the comparison probability is greater than the probability threshold, the registered user is determined to be the target user; and if the comparison probability is smaller than the probability threshold, determining that the registered user is not the target user.
According to the embodiment of the present invention, the user determination method further includes: and updating the historical behavior path data set according to the behavior path data of the registered user and the application service completion probability of the registered user.
According to a specific implementation manner of the embodiment of the present invention, in a case that the operation historical behavior path data set is a historical behavior path model, after the historical behavior path model is constructed, the historical behavior path model may be retrained again according to corresponding data (mainly referring to a user portrait, behavior path data, and application service completion) of a registered user compared by a determined target user, so as to optimize the historical behavior path model and improve accuracy of the determined target user.
According to the technical scheme of the embodiment of the invention, the user portrait of the registered user is obtained; acquiring behavior path data of a registered user; the user portrait of the registered user and the behavior path data are compared by utilizing the historical behavior path data set to determine the target user, wherein the historical behavior path data set indicates the application service completion probability corresponding to the historical behavior path data, and the target user refers to the technical means of the registered user meeting the threshold of the application service completion probability, so that the technical problems that in the prior art, the target client is determined only through a single behavior when the user accesses the application, the workload of a user determination method is large, and the accuracy of the determined target user is low are solved, the workload of user determination is reduced, and the accuracy of the determined target user is improved.
FIG. 3 is a schematic diagram of the main modules of a user determination device according to an embodiment of the invention; as shown in fig. 3, the user determination apparatus 300 according to the embodiment of the present invention mainly includes:
target user determination module 301 for obtaining a user representation of a registered user.
Specifically, according to the embodiment of the present invention, the user representation includes user attribute information and user behavior information.
Wherein the user attribute information includes: basic attribute information such as age, gender, occupation, and user number of the user. The user behavior information includes information such as individual behavior (click behavior) when the user accesses the application, frequency of the click behavior, access times, and time stamps corresponding to the respective click behaviors.
Registering a user: the user who completes registration in the application program but does not execute the corresponding application service, for example, the user who completes registration in a mail application program but does not execute the mail service.
A behavior path data obtaining module 302, configured to obtain behavior path data of the registered user.
Further, according to an embodiment of the present invention, the behavior path data obtaining module 302 is further configured to: and determining behavior path data of the registered user for accessing the application once according to the time threshold and the time stamp of each click behavior when the registered user accesses the application, and acquiring the behavior path data.
In a complete behavior path data, a user may briefly quit the application due to other factors (network delay, checking other application information, and the like) during the process of accessing the application to perform a corresponding click behavior operation, in order to obtain a relatively complete behavior path data, by setting a time threshold, after a registered user accesses the application, the click behaviors of the user are sorted according to a timestamp corresponding to each click behavior of the registered user, if a time interval between the current user behavior and the last user behavior is greater than the time threshold, the current access is considered to be finished, and the currently obtained user behavior sorting is determined as the behavior path data corresponding to the current access.
And the target user determining module 303 is configured to compare the user portrait of the registered user with the behavior path data by using a historical behavior path data set to determine a target user, where the historical behavior path data set indicates an application service completion probability corresponding to the historical behavior path data, and the target user refers to a registered user meeting an application service completion probability threshold.
Specifically, according to the user portrait of the registered user and the behavior path data, the user portrait corresponding to the historical user and the historical behavior path data are compared in the historical behavior path data set to determine the target user. According to a specific implementation manner of the embodiment of the invention, the comparison probability can be obtained through comparison, and if the comparison probability is greater than the probability threshold, the registered user is determined to be the target user; and if the comparison probability is smaller than the probability threshold, determining that the registered user is not the target user.
Specifically, according to an embodiment of the present invention, the user determination apparatus 300 further includes a historical behavior path data set construction module, and before the step of comparing the user portrait of the registered user with the behavior path data by using the historical behavior path data set, the user determination method further includes:
acquiring a user portrait of a historical user;
determining historical behavior path data corresponding to a historical user, wherein the historical behavior path data indicates the completion probability of the application service of the historical user;
a historical behavior path data set is constructed based on the user representation of the historical user and the historical behavior path data.
History users: the users who have completed registration in the application program include users who do not execute the application service and users who have executed the application service. I.e. the historical users comprise registered users.
The historical behavior path data set is constructed through historical data (namely user figures of historical users and behavior path data of the historical users), and the accuracy of the determined target users is obviously improved.
According to an embodiment of the present invention, the historical behavior path data includes first historical behavior path data, and the step of determining the historical behavior path data corresponding to the historical user includes: and determining first historical behavior path data according to historical clicking behaviors of historical users, corresponding timestamps of the historical clicking behaviors and application service completion probability thresholds, wherein the number of the first historical behavior path data is at least one.
The data used to construct the historical behavior path dataset may include multiple types. The first historical behavior path data is simple and direct to obtain, a plurality of historical behavior path data can be directly determined according to the historical behavior data of the historical user and the time stamps corresponding to the historical behaviors, and then the first historical behavior path data is determined from the plurality of historical behavior path data according to the application service completion threshold. According to a specific implementation manner of the embodiment of the present invention, several pieces of historical behavior path data (a specific determination process may adopt a statistical analysis manner) with a high application service completion degree may be determined as the first historical behavior path data.
Further, according to an embodiment of the present invention, the historical behavior path data further includes second historical behavior path data and third historical behavior path data, and the step of determining the historical behavior path data corresponding to the historical user further includes: determining second historical behavior path data according to the association rule; and determining third history behavior path data according to the due business rules.
Specifically, the first historical behavior path data is determined primarily by means of statistical analysis of the historical data (i.e., based on an application traffic completion threshold). However, the historical behavior path data determined only in the above manner has the disadvantages of long behavior path and no representativeness. In order to further improve the optimization degree of the constructed historical behavior path data set, the accuracy of the determined target user is improved. And identifying two click behaviors which are influential and strongly associated with each other through the association rule, and determining the two click behaviors which meet the conditions as second historical behavior path data.
Meanwhile, third history behavior path data can be determined according to key behaviors given by the target business behaviors according to the time stamp sequence.
Association rules: in the process of accessing the application, if influence and strong correlation exist between two clicking behaviors, even if the two behaviors do not occur closely, the behavior path data can be determined according to the time stamp sequence corresponding to the two behaviors.
And (3) application business behavior: refers to the click behavior that a user must (inevitably) perform when completing the application service of its registered application.
According to an embodiment of the present invention, the user determining apparatus 300 further includes an updating module, configured to update the historical behavior path data set according to the behavior path data of the registered user and the application service completion probability of the registered user.
According to a specific implementation manner of the embodiment of the present invention, in a case that the historical behavior path data set is the historical behavior path model, after the historical behavior path model is constructed, the historical behavior path model may be retrained again according to corresponding data (mainly referring to the user portrait, the behavior path data, and the application service completion degree) of a registered user compared by a determined target user, so as to optimize the historical behavior path model and improve the accuracy of the determined target user.
According to the technical scheme of the embodiment of the invention, the user portrait of the registered user is obtained; acquiring behavior path data of a registered user; the user portrait of the registered user and the behavior path data are compared by utilizing the historical behavior path data set to determine the target user, wherein the historical behavior path data set indicates the application service completion probability corresponding to the historical behavior path data, and the target user refers to the technical means of the registered user meeting the threshold of the application service completion probability, so that the technical problems that in the prior art, the target client is determined only through a single behavior when the user accesses the application, the workload of a user determination method is large, and the accuracy of the determined target user is low are solved, the workload of user determination is reduced, and the accuracy of the determined target user is improved.
Fig. 4 illustrates an exemplary system architecture 400 to which the user determination method or user determination apparatus of embodiments of the invention may be applied.
As shown in fig. 4, the system architecture 400 may include terminal devices 401, 402, 403, a network 404, and a server 405 (this architecture is merely an example, and the components included in a particular architecture may be adapted according to application specific circumstances). The network 404 serves as a medium for providing communication links between the terminal devices 401, 402, 403 and the server 405. Network 404 may include various types of connections, such as wire, wireless communication links, or fiber optic cables, to name a few.
A user may use terminal devices 401, 402, 403 to interact with a server 405 over a network 404 to receive or send messages or the like. The terminal devices 401, 402, 403 may have installed thereon various communication client applications, such as shopping-like applications, web browser applications, search-like applications, instant messaging tools, mailbox clients, social platform software, etc. (by way of example only).
The terminal devices 401, 402, 403 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 405 may be a server providing various services, such as a background management server (for example only) providing support for shopping websites browsed by users using the terminal devices 401, 402, 403. The backend management server may analyze and otherwise process the received user profile, behavior path data, and other data, and feed back the processing results (e.g., the target user — just an example) to the terminal device.
It should be noted that the user determination method provided by the embodiment of the present invention is generally executed by the server 405, and accordingly, the user determination apparatus is generally disposed in the server 405.
It should be understood that the number of terminal devices, networks, and servers in fig. 4 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Referring now to FIG. 5, shown is a block diagram of a computer system 500 suitable for use with a terminal device implementing an embodiment of the present invention. The terminal device shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 5, the computer system 500 includes a Central Processing Unit (CPU)501 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)502 or a program loaded from a storage section 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data necessary for the operation of the system 500 are also stored. The CPU 501, ROM 502, and RAM 503 are connected to each other via a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
The following components are connected to the I/O interface 505: an input portion 506 including a keyboard, a mouse, and the like; an output portion 507 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 508 including a hard disk and the like; and a communication section 509 including a network interface card such as a LAN card, a modem, or the like. The communication section 509 performs communication processing via a network such as the internet. The driver 510 is also connected to the I/O interface 505 as necessary. A removable medium 511 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 510 as necessary, so that a computer program read out therefrom is mounted into the storage section 508 as necessary.
In particular, according to the embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 509, and/or installed from the removable medium 511. The computer program performs the above-described functions defined in the system of the present invention when executed by the Central Processing Unit (CPU) 501.
It should be noted that the computer readable medium shown in the present invention can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules described in the embodiments of the present invention may be implemented by software or hardware. The described modules may also be provided in a processor, which may be described as: a processor includes a user representation acquisition module, a behavioral path data acquisition module, and a target user determination module. Where the names of these modules do not in some cases constitute a limitation on the module itself, for example, the target user determination module may also be described as a "module for obtaining a user representation of a registered user".
As another aspect, the present invention also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be separate and not incorporated into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to comprise: acquiring a user portrait of a registered user; acquiring behavior path data of a registered user; comparing the user portrait of the registered user with the behavior path data by using a historical behavior path data set to determine a target user, wherein the historical behavior path data set indicates the application service completion probability corresponding to the historical behavior path data, and the target user refers to the registered user meeting the application service completion probability threshold.
According to the technical scheme of the embodiment of the invention, the user portrait of the registered user is obtained; acquiring behavior path data of a registered user; the user portrait of the registered user and the behavior path data are compared by utilizing the historical behavior path data set to determine the target user, wherein the historical behavior path data set indicates the application service completion probability corresponding to the historical behavior path data, and the target user refers to the technical means of the registered user meeting the threshold of the application service completion probability, so that the technical problems that in the prior art, the target client is determined only through a single behavior when the user accesses the application, the workload of a user determination method is large, and the accuracy of the determined target user is low are solved, the workload of user determination is reduced, and the accuracy of the determined target user is improved.
The above-described embodiments should not be construed as limiting the scope of the invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions can occur, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method for user determination, comprising:
acquiring a user portrait of a registered user;
acquiring behavior path data of the registered user;
comparing the user portrait of the registered user with the behavior path data by using a historical behavior path data set to determine a target user, wherein the historical behavior path data set indicates the application service completion probability corresponding to the historical behavior path data, and the target user refers to the registered user meeting the application service completion probability threshold.
2. The user determination method according to claim 1, wherein the step of obtaining the behavior path data of the registered user comprises: and determining the behavior path data of the registered user accessing the application once according to the time threshold and the time stamp of each click behavior when the registered user accesses the application, and acquiring the behavior path data.
3. The user determination method according to claim 1 or 2, wherein before the step of comparing the user representation and the behavior path data of the registered user with the historical behavior path data set, the user determination method further comprises:
acquiring a user portrait of a historical user;
determining historical behavior path data corresponding to the historical user, wherein the historical behavior path data indicates the completion probability of the application service of the historical user;
and constructing a historical behavior path data set based on the user portrait of the historical user and the historical behavior path data.
4. The method of claim 3, wherein the historical behavior path data comprises first historical behavior path data, and wherein determining the historical behavior path data corresponding to the historical user comprises: and determining the first historical behavior path data according to the historical clicking behaviors of the historical users, corresponding timestamps of the historical clicking behaviors and application service completion probability thresholds, wherein the number of the first historical behavior path data is at least one.
5. The method of claim 3, wherein the historical behavior path data further comprises second historical behavior path data and third historical behavior path data, and the step of determining the historical behavior path data corresponding to the historical user further comprises: determining the second historical behavior path data according to an association rule; and determining the third history behavior path data according to due business rules.
6. The user determination method of claim 1, wherein the user representation includes user attribute information and user behavior information.
7. The user determination method according to claim 1, further comprising: and updating the historical behavior path data set according to the behavior path data of the registered user and the application service completion probability of the registered user.
8. A user determination device, comprising:
the user portrait acquisition module is used for acquiring a user portrait of a registered user;
a behavior path data acquisition module, configured to acquire behavior path data of the registered user;
and the target user determining module is used for comparing the user portrait of the registered user with the behavior path data by utilizing a historical behavior path data set to determine a target user, wherein the historical behavior path data set indicates the application service completion probability corresponding to the historical behavior path data, and the target user refers to the registered user meeting the application service completion probability threshold.
9. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-7.
10. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1-7.
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