CN113362097B - User determination method and device - Google Patents

User determination method and device Download PDF

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CN113362097B
CN113362097B CN202010151941.0A CN202010151941A CN113362097B CN 113362097 B CN113362097 B CN 113362097B CN 202010151941 A CN202010151941 A CN 202010151941A CN 113362097 B CN113362097 B CN 113362097B
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user
path data
behavior path
historical
historical behavior
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CN113362097A (en
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黄倩
刘洋
姜婷
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Beijing Jingdong Zhenshi Information Technology Co Ltd
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Beijing Jingdong Zhenshi Information Technology Co Ltd
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce
    • G06Q30/02Marketing; Price estimation or determination; Fundraising
    • G06Q30/0241Advertisements
    • G06Q30/0251Targeted advertisements
    • G06Q30/0255Targeted advertisements based on user history
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce
    • G06Q30/02Marketing; Price estimation or determination; Fundraising
    • G06Q30/0241Advertisements
    • G06Q30/0251Targeted advertisements
    • G06Q30/0254Targeted advertisements based on statistics

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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 the following steps: acquiring a user portrait of a registered user; acquiring behavior path data of a registered user; and comparing the user portrait of the registered user with the behavior path data by using the 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 is the registered user meeting the application service completion probability threshold. According to the embodiment, the workload of user determination is reduced, and the accuracy of the determined target user is improved.

Description

User determination method and device
Technical Field
The present invention relates to the field of computer technologies, and in particular, to a user determining method and apparatus.
Background
With the development of internet technology, more and more companies are beginning 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 on the basis of potential users.
In the process of implementing the present 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 action when a user accesses an application, the workload of a user determination method is large, and the accuracy of the determined target user is low.
Disclosure of Invention
In view of the above, the embodiments of the present invention provide a user determining method and apparatus, which can reduce the workload of user determination and improve the accuracy of the determined target user.
To achieve the above object, according to a first aspect of an embodiment 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;
and comparing the user portrait of the registered user with the behavior path data by using the 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 is the registered user meeting the application service completion probability threshold.
Further, the step of acquiring behavior path data of the registered user includes: and determining behavior path data of the application accessed by the registered user for one time according to the time threshold and the time stamp of each clicking action when the registered user accesses the application, and acquiring the behavior path data.
Further, before the step of comparing the user portraits and the behavior path data of the registered users using 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 a historical user, wherein the historical behavior path data indicates the probability of the completion of the application business of the historical user;
a historical behavior path dataset 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 the historical click behaviors of the historical users and the corresponding time stamps and the application service completion probability thresholds, wherein 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 historical behavior path data according to the due business rule.
Further, the user profile 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 an embodiment of the present invention, there is provided a user determination apparatus including:
the target user determining module is used for acquiring the user portrait of the registered user;
the behavior path data acquisition module is used for acquiring 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 indicates the registered user meeting the application service completion probability threshold.
According to a third aspect of an embodiment of the present invention, there is provided an electronic apparatus including:
one or more processors;
storage means for storing one or more programs,
the one or more programs, when executed by the 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 having stored thereon a computer program which when executed by a processor implements a user determination method as any one of the above.
One embodiment of the above invention has the following advantages or benefits: because a user portrait is taken for the registered user; acquiring behavior path data of a registered user; the user portrait of the registered user is compared with the behavior path data by using 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 indicates the technical means of the registered user meeting the application service completion probability threshold, so that the technical effects that the target client is determined only through a single behavior when the user accesses the application in the prior art are overcome, the technical problems that 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 are further achieved.
Further effects of the above-described non-conventional alternatives are described below in connection with the embodiments.
Drawings
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 the main flow of a user determination method provided according to a first embodiment of the present invention;
FIG. 2 is a schematic diagram of the 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 present invention;
FIG. 4 is an exemplary system architecture diagram in which embodiments of the present invention may be applied;
fig. 5 is a schematic diagram of a computer system suitable for use in implementing an embodiment of the invention.
Detailed Description
Exemplary embodiments of the present invention will now be described with reference to the accompanying drawings, in which various details of the embodiments of the present invention are included to facilitate understanding, and are to be considered 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 the main flow of a user determination method provided according to a first embodiment of the present invention; as shown in fig. 1, the user determining method provided by the embodiment of the present invention mainly includes:
Step S101, a user portrait of a registered user is acquired.
Specifically, according to an embodiment of the present invention, the user portrait includes user attribute information and user behavior information.
Wherein the user attribute information includes: basic attribute information such as age, sex, occupation, user number, and the like 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, the number of accesses, time stamp corresponding to each click behavior, and the like.
Registering a user: a user who completes registration in an application but does not execute a corresponding application service, such as a user who completes registration in a consignment application but does not execute consignment service.
Step S102, behavior path data of a registered user is acquired.
Further, according to an embodiment of the present invention, the step of obtaining behavior path data of the registered user includes: and determining behavior path data of the application accessed by the registered user for one time according to the time threshold and the time stamp of each clicking action when the registered user accesses the application, and acquiring the behavior path data.
In the complete behavior path data, a user may temporarily exit the application due to other factors (network delay, other application information viewing, etc.) in the process of performing corresponding clicking behavior operation on the access application, in order to obtain relatively complete behavior path data, after the user access application is registered, the clicking behaviors of the user are ordered according to the time stamp corresponding to each clicking behavior of the registered user, if the 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 ended, and the currently obtained user behavior ordering is determined as the behavior path data corresponding to the current access.
Step S103, 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 indicates the registered user meeting the application service completion probability threshold.
Specifically, according to the user portrait and the behavior path data of the registered user, the user portrait corresponding to the historical user in the historical behavior path data set is compared with the historical behavior path data to determine the target user. According to a specific implementation manner of the embodiment of the present invention, the comparison probability may be obtained by comparison, and if the comparison probability is greater than a probability threshold, the registered user is determined to be a target user; and if the comparison probability is smaller than the probability threshold value, determining that the registered user is not a target user.
Specifically, according to an embodiment of the present invention, before the step of comparing the user portraits and the behavior path data of the registered users 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 probability of the completion of the application business of the historical user;
A historical behavior path dataset is constructed based on the user representation of the historical user and the historical behavior path data.
History user: refers to a user who has completed registration in an application program, and includes a user who has not executed an application service and a user who has executed an application service. I.e. the history user comprises registered users.
The historical behavior path data set is constructed through the historical data (namely the user portrait of the historical user and the behavior path data of the historical user), so that the accuracy of the determined target user is remarkably 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 the historical click behaviors of the historical users and the corresponding time stamps and the application service completion probability thresholds, wherein the first historical behavior path data is at least one.
The data used to construct the historical behavioral path dataset may include a plurality of types. The first historical behavior path data is simpler and more direct to acquire, a plurality of historical behavior path data can be determined directly according to the historical behavior data of the historical user and the time stamp corresponding to the historical behavior, and then the first historical behavior path data is determined from the plurality of historical behavior path data according to the application business completion degree threshold. According to a specific implementation manner of the embodiment of the present invention, the above-mentioned several historical behavior path data with higher application service completion degrees (a specific judgment process may adopt a statistical analysis manner) 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 historical behavior path data according to the due business rule.
In particular, 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 disadvantage of long behavior paths and no typical behavior paths. In order to further improve the degree of optimization of the constructed historical behavior path data set, the accuracy of the determined target user is improved. And identifying two click behaviors which have influence and strong association with each other through association rules, and determining the two click behaviors which meet the conditions as second historical behavior path data.
Meanwhile, the third historical behavior path data can be determined according to the key behaviors given by the target business behaviors and 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 in close proximity, the behavior path data can be determined according to the time stamp sequence corresponding to the two behaviors.
Application business behavior: refers to the clicking action that a user must (inevitably) perform when completing the application service of his registered application.
According to an embodiment of the present invention, the above 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 the case that the operation historical behavior path dataset is a historical behavior path model, after the construction of the historical behavior path model is completed, the historical behavior path model may be retrained according to corresponding data (mainly referred to as user portrait, behavior path data and application service completion degree) of the registered user compared with the 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 acquired; acquiring behavior path data of a registered user; the user portrait of the registered user is compared with the behavior path data by using 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 indicates the technical means of the registered user meeting the application service completion probability threshold, so that the technical effects that the target client is determined only through a single behavior when the user accesses the application in the prior art are overcome, the technical problems that 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 are further achieved.
FIG. 2 is a schematic diagram of the 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 various Application programs, and the Application scenario of this embodiment is an Application (Application) app. As shown in fig. 2, the user determining method provided by the embodiment of the present invention mainly includes:
step S201, user portraits of a history user are acquired.
Specifically, according to an embodiment of the present invention, the user portrait includes user attribute information and user behavior information.
Wherein the user attribute information includes: basic attribute information such as age, sex, occupation, user number, and the like 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, the number of accesses, time stamp corresponding to each click behavior, and the like.
History user: refers to a user who has completed registration in an application program, and includes a user who has not executed an application service and a user who has executed an application service. I.e. the history user comprises registered users.
Step S202, determining behavior path data of a historical user, wherein the historical behavior path data indicates the probability of the completion of the application business of the historical user.
Further, according to an embodiment of the present invention, the step of obtaining behavior path data of an application user includes: and determining behavior path data of the application accessed by the registered user for one time according to the time threshold and the time stamp of each clicking action when the registered user accesses the application, and acquiring the behavior path data.
In the complete behavior path data, a user may temporarily exit the application due to other factors (network delay, other application information viewing, etc.) in the process of performing corresponding clicking behavior operation on the access application, in order to obtain relatively complete behavior path data, after the user access application is registered, the clicking behaviors of the user are ordered according to the time stamp corresponding to each clicking behavior of the registered user, if the 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 ended, and the currently obtained user behavior ordering 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 portraits of the historical users and the historical behavior path data.
The historical behavior path data set is constructed through the historical data (namely the user portrait of the historical user and the historical behavior path data of the historical user), so that the accuracy of the determined target user is remarkably 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 the historical click behaviors of the historical users and the corresponding time stamps and the application service completion probability thresholds, wherein the first historical behavior path data is at least one.
The data used to construct the historical behavioral path dataset may include a plurality of types. The first historical behavior path data is simpler and more direct to acquire, a plurality of historical behavior path data can be determined directly according to the historical behavior data of the historical user and the time stamp corresponding to the historical behavior, and then the first historical behavior path data is determined from the plurality of historical behavior path data according to the application business completion degree threshold. According to a specific implementation manner of the embodiment of the present invention, the above-mentioned several historical behavior path data with higher application service completion degrees (a specific judgment process may adopt a statistical analysis manner) 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 historical behavior path data according to the due business rule.
In particular, 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 disadvantage of long behavior paths and no typical behavior paths. In order to further improve the degree of optimization of the constructed historical behavior path data set, the accuracy of the determined target user is improved. And identifying two click behaviors which have influence and strong association with each other through association rules, and determining the two click behaviors which meet the conditions as second historical behavior path data.
Meanwhile, the third historical behavior path data can be determined according to the key behaviors given by the target business behaviors and 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 in close proximity, the behavior path data can be determined according to the time stamp sequence corresponding to the two behaviors.
Application business behavior: refers to the clicking action that a user must (inevitably) perform when completing the application service of his registered application.
According to the embodiment of the invention, the step of constructing the historical behavior path data set can also construct a historical behavior path model, specifically, a logistic regression algorithm and an xgboost algorithm (extreme gradient lifting algorithm) can be adopted to construct the historical behavior path model, and an existing model construction method can 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 (the historical behavior path data is a two-class variable, i.e., each historical behavior path data variable corresponds to 0 and 1 respectively, wherein 1 represents a behavior path indicated by the historical behavior path data when the application service is completed, and 0 represents a behavior path indicated by the historical behavior path data when the application service is completed) are taken as independent variables, so as to construct a historical behavior path model.
Step S204, a user portrait of the registered user is acquired.
Registering a user: a user who completes registration in an application but does not perform an application service, such as a user who completes registration in a consignment application but does not perform consignment service.
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 the 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 indicates the registered user meeting the application service completion probability threshold.
Specifically, according to the user portrait and the behavior path data of the registered user, the user portrait corresponding to the historical user in the historical behavior path data set is compared with the historical behavior path data to determine the target user. According to a specific implementation manner of the embodiment of the present invention, the comparison probability may be obtained by comparison, and if the comparison probability is greater than a probability threshold, the registered user is determined to be a target user; and if the comparison probability is smaller than the probability threshold value, determining that the registered user is not a target user.
According to an embodiment of the present invention, the above 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 the case that the operation historical behavior path dataset is a historical behavior path model, after the construction of the historical behavior path model is completed, the historical behavior path model may be retrained according to corresponding data (mainly referred to as user portrait, behavior path data and application service completion degree) of the registered user compared with the 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 acquired; acquiring behavior path data of a registered user; the user portrait of the registered user is compared with the behavior path data by using 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 indicates the technical means of the registered user meeting the application service completion probability threshold, so that the technical effects that the target client is determined only through a single behavior when the user accesses the application in the prior art are overcome, the technical problems that 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 are further achieved.
FIG. 3 is a schematic diagram of the main modules of a user determination device according to an embodiment of the present invention; as shown in fig. 3, the user determining apparatus 300 provided in the embodiment of the present invention mainly includes:
the target user determining module 301 is configured to obtain a user portrait of a registered user.
Specifically, according to an embodiment of the present invention, the user portrait includes user attribute information and user behavior information.
Wherein the user attribute information includes: basic attribute information such as age, sex, occupation, user number, and the like 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, the number of accesses, time stamp corresponding to each click behavior, and the like.
Registering a user: a user who completes registration in an application but does not execute a corresponding application service, such as a user who completes registration in a consignment application but does not execute consignment service.
The behavior path data acquisition module 302 is configured to acquire behavior path data of a registered user.
Further, according to an embodiment of the present invention, the behavior path data acquisition module 302 is further configured to: and determining behavior path data of the application accessed by the registered user for one time according to the time threshold and the time stamp of each clicking action when the registered user accesses the application, and acquiring the behavior path data.
In the complete behavior path data, a user may temporarily exit the application due to other factors (network delay, other application information viewing, etc.) in the process of performing corresponding clicking behavior operation on the access application, in order to obtain relatively complete behavior path data, after the user access application is registered, the clicking behaviors of the user are ordered according to the time stamp corresponding to each clicking behavior of the registered user, if the 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 ended, and the currently obtained user behavior ordering is determined as the behavior path data corresponding to the current access.
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 the registered user that meets an application service completion probability threshold.
Specifically, according to the user portrait and the behavior path data of the registered user, the user portrait corresponding to the historical user in the historical behavior path data set is compared with the historical behavior path data to determine the target user. According to a specific implementation manner of the embodiment of the present invention, the comparison probability may be obtained by comparison, and if the comparison probability is greater than a probability threshold, the registered user is determined to be a target user; and if the comparison probability is smaller than the probability threshold value, determining that the registered user is not a target user.
Specifically, according to an embodiment of the present invention, the user determining apparatus 300 further includes a historical behavior path data set construction module, and before the step of comparing the user representation of the registered user with the behavior path data by using the historical behavior path data set, the user determining 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 probability of the completion of the application business of the historical user;
a historical behavior path dataset is constructed based on the user representation of the historical user and the historical behavior path data.
History user: refers to a user who has completed registration in an application program, and includes a user who has not executed an application service and a user who has executed an application service. I.e. the history user comprises registered users.
The historical behavior path data set is constructed through the historical data (namely the user portrait of the historical user and the behavior path data of the historical user), so that the accuracy of the determined target user is remarkably 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 the historical click behaviors of the historical users and the corresponding time stamps and the application service completion probability thresholds, wherein the first historical behavior path data is at least one.
The data used to construct the historical behavioral path dataset may include a plurality of types. The first historical behavior path data is simpler and more direct to acquire, a plurality of historical behavior path data can be determined directly according to the historical behavior data of the historical user and the time stamp corresponding to the historical behavior, and then the first historical behavior path data is determined from the plurality of historical behavior path data according to the application business completion degree threshold. According to a specific implementation manner of the embodiment of the present invention, the above-mentioned several historical behavior path data with higher application service completion degrees (a specific judgment process may adopt a statistical analysis manner) 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 historical behavior path data according to the due business rule.
In particular, 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 disadvantage of long behavior paths and no typical behavior paths. In order to further improve the degree of optimization of the constructed historical behavior path data set, the accuracy of the determined target user is improved. And identifying two click behaviors which have influence and strong association with each other through association rules, and determining the two click behaviors which meet the conditions as second historical behavior path data.
Meanwhile, the third historical behavior path data can be determined according to the key behaviors given by the target business behaviors and 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 in close proximity, the behavior path data can be determined according to the time stamp sequence corresponding to the two behaviors.
Application business behavior: refers to the clicking action that a user must (inevitably) perform when completing the application service of his 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 the case that the above-mentioned historical behavior path dataset is a historical behavior path model, after the historical behavior path model is built, the historical behavior path model may be retrained according to corresponding data (mainly referred to as user portrait, behavior path data and application service completion degree) of the registered user compared with the 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 acquired; acquiring behavior path data of a registered user; the user portrait of the registered user is compared with the behavior path data by using 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 indicates the technical means of the registered user meeting the application service completion probability threshold, so that the technical effects that the target client is determined only through a single behavior when the user accesses the application in the prior art are overcome, the technical problems that 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 are further achieved.
Fig. 4 illustrates an exemplary system architecture 400 in which a user-determined method or user-determined apparatus of embodiments of the present invention may be applied.
As shown in fig. 4, a 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 contained in a particular architecture may be tailored to the application specific case). The network 404 is used as a medium to provide communication links between the terminal devices 401, 402, 403 and the server 405. The network 404 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.
A user may interact with the server 405 via the network 404 using the terminal devices 401, 402, 403 to receive or send messages or the like. Various communication client applications, such as shopping class applications, web browser applications, search class applications, instant messaging tools, mailbox clients, social platform software, etc. (by way of example only) may be installed on the terminal devices 401, 402, 403.
The terminal devices 401, 402, 403 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smartphones, tablets, laptop and desktop computers, and the like.
The server 405 may be a server providing various services, such as a background management server (by way of example only) providing support for shopping-type websites browsed by users using the terminal devices 401, 402, 403. The background management server may analyze and other data such as the received user portraits, behavior path data, etc., 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 determining method provided in the embodiment of the present invention is generally performed by the server 405, and accordingly, the user determining device 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, there is illustrated a schematic diagram of a computer system 500 suitable for use in implementing an embodiment of the present invention. The terminal device shown in fig. 5 is only an example, and should not impose any limitation on the functions and the scope of use of the embodiment of the present invention.
As shown in fig. 5, the computer system 500 includes a Central Processing Unit (CPU) 501, which 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 required for the operation of the system 500 are also stored. The CPU 501, ROM 502, and RAM 503 are connected to each other through 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 section 506 including a keyboard, a mouse, and the like; an output portion 507 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker, and the like; 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 drive 510 is also connected to the I/O interface 505 as needed. 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 needed so that a computer program read therefrom is mounted into the storage section 508 as needed.
In particular, according to embodiments of the present disclosure, the processes described above with reference to 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 shown in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication portion 509, and/or installed from the removable media 511. The above-described functions defined in the system of the present invention are performed when the computer program is executed by a Central Processing Unit (CPU) 501.
The computer readable medium shown in the present invention may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any 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 context of this document, 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, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. 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 flowcharts 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 involved in the embodiments of the present invention may be implemented in software or in hardware. The described modules may also be provided in a processor, for example, as: a processor includes a user representation acquisition module, a behavior path data acquisition module, and a target user determination module. The names of these modules do not constitute a limitation on the module itself in some cases, and for example, the target user determination module may also be described as "a module for acquiring 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 present alone without being fitted into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to include: acquiring a user portrait of a registered user; acquiring behavior path data of a registered user; and comparing the user portrait of the registered user with the behavior path data by using the 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 is 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 acquired; acquiring behavior path data of a registered user; the user portrait of the registered user is compared with the behavior path data by using 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 indicates the technical means of the registered user meeting the application service completion probability threshold, so that the technical effects that the target client is determined only through a single behavior when the user accesses the application in the prior art are overcome, the technical problems that 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 are further achieved.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives can occur depending upon design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.

Claims (8)

1. A method of user determination, comprising:
acquiring a user portrait of a registered user;
acquiring behavior path data of the registered user;
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 probability of the completion of the application business of the historical user; constructing a historical behavior path data set based on the user representation of the historical user and the historical behavior path data;
comparing the user portrait of the registered user with 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 is the registered user meeting the application service completion probability threshold; wherein the historical behavior path data in the historical behavior path data set comprises second historical behavior path data and third historical behavior path data;
The determining step of the second historical behavior path data includes: identifying two click behaviors which have influence and strong association with each other through association rules, and determining the two click behaviors which meet the conditions as the second historical behavior path data;
the determining step of the third historical behavior path data includes: and determining the third historical behavior path number according to the key behaviors given by the target business behaviors and the time stamp sequence.
2. The user determination method according to claim 1, wherein the step of acquiring the behavior path data of the registered user includes: and determining behavior path data of the single access application of the registered user according to a time threshold and time stamps of clicking behaviors when the registered user accesses the application, and acquiring the behavior path data.
3. The user determination method according to claim 1, wherein 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 the first historical behavior path data according to the historical click behaviors of the historical users and the corresponding time stamps and the application service completion probability thresholds, wherein the first historical behavior path data is at least one.
4. The user determination method of claim 1, wherein the user representation includes user attribute information and user behavior information.
5. The user determination method according to claim 1, characterized in that the user determination method further comprises: 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.
6. A user-defined device, comprising:
the user portrait acquisition module is used for acquiring user portraits of registered users;
the behavior path data acquisition module is used for acquiring the behavior path data of the registered user;
the target user determining module is used for acquiring user portraits of the historical users; determining historical behavior path data corresponding to the historical user, wherein the historical behavior path data indicates the probability of the completion of the application business of the historical user; constructing a historical behavior path data set based on the user representation of the historical user and the historical behavior path data; comparing the user portrait of the registered user with 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 is the registered user meeting the application service completion probability threshold; wherein the historical behavior path data in the historical behavior path data set comprises second historical behavior path data and third historical behavior path data; the determining step of the second historical behavior path data includes: identifying two click behaviors which have influence and strong association with each other through association rules, and determining the two click behaviors which meet the conditions as the second historical behavior path data; the determining step of the third historical behavior path data includes: and determining the third historical behavior path number according to the key behaviors given by the target business behaviors and the time stamp sequence.
7. An electronic device, comprising:
one or more processors;
storage means for storing one or more programs,
when executed by the one or more processors, causes the one or more processors to implement the method of any of claims 1-5.
8. A computer readable medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the method according to any of claims 1-5.
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