CN111915366A - User portrait construction method and device, computer equipment and storage medium - Google Patents
User portrait construction method and device, computer equipment and storage medium Download PDFInfo
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Abstract
The invention discloses a user portrait construction method, a device, computer equipment and a storage medium, wherein the method comprises the following steps: acquiring user data of a user to be imaged, and generating a basic label of the user to be imaged according to the user data, wherein the user data at least comprises basic data and behavior data of the user to be imaged; performing combined calculation on the basic labels through a pre-trained label model to generate a composite label of the user to be imaged; and generating an individual portrait corresponding to the user to be pictured according to the basic label, the composite label and the portrait type of the user to be pictured. According to the invention, the corresponding user portrait is constructed for each application scene, so that the user characteristics can be accurately and rapidly identified, accurate service is provided for the user, and the user experience is improved.
Description
Technical Field
The invention relates to the technical field of user portraits, in particular to a user portraits construction method, a user portraits construction device, computer equipment and a storage medium.
Background
The user portrait is also called a user role and is an effective tool for delineating target users and connecting user appeal and design direction, and the user portrait is widely applied to various fields. In the actual operation process, the attributes, behaviors and expectations of the user are often combined by the words which are most shallow and close to life. As a virtual representation of an actual user, the user roles formed by user portrayal are not constructed outside products and markets, and the formed user roles need to represent the main audience and target groups of the products.
With the rapid development of the logistics industry and the gradual business digitization of enterprises, the user data of the logistics system is more and more huge. At present, in the logistics industry, there is no perfect stereo image analysis, and currently, the method is only generally used for type classification of terminal couriers, and no more comprehensive and deeper image system exists. In the face of huge user data, how to construct a corresponding user portrait for each application scenario so as to be able to accurately and quickly identify user characteristics, and how to provide accurate service for key customers so as to improve user experience, etc. are urgent needs to be solved at present.
Disclosure of Invention
In order to solve the problems in the prior art, embodiments of the present invention provide a user portrait construction method and apparatus, a computer device, and a storage medium, so as to overcome the problems in the prior art that it is difficult to accurately and quickly identify characteristics of a client in the presence of a large amount of user data, and user experience cannot be improved due to the inability to provide accurate services for key clients.
In order to solve one or more technical problems, the invention adopts the technical scheme that:
in a first aspect, a user representation construction method is provided, which includes the following steps:
acquiring user data of a user to be imaged, and generating a basic label of the user to be imaged according to the user data, wherein the user data at least comprises basic data and behavior data of the user to be imaged;
performing combined calculation on the basic labels through a pre-trained label model to generate a composite label of the user to be imaged;
and generating an individual portrait corresponding to the user to be pictured according to the basic label, the composite label and the portrait type of the user to be pictured.
Further, the acquiring the user data of the user to be imaged includes:
analyzing logistics information of a user to be imaged in a logistics system to obtain basic data of the user to be imaged;
and acquiring the behavior data of the user to be imaged from a third-party data source according to the basic data.
Further, the generating an individual portrait corresponding to the user to be pictured according to the basic tag, the composite tag, and the portrait type of the user to be pictured includes:
and matching and acquiring a target label corresponding to the portrait type from the basic label and the composite label, and generating the individual portrait of the user to be pictured according to the target label.
Further, the method further comprises:
and classifying the individual pictures through a pre-trained classification model, the basic labels and the composite labels to generate a group picture corresponding to the user to be pictured.
Further, the method further comprises:
receiving a first query request sent by a request end, wherein the first query request at least comprises information of a tag to be matched;
and inquiring the individual portrait corresponding to the label information to be matched and returning the individual portrait to the request end.
Further, the method further comprises:
receiving a second query request sent by a request end, wherein the second query request at least comprises the individual portrait information to be matched:
and querying the group portrait corresponding to the individual portrait information to be matched and returning the group portrait to the request end.
In a second aspect, there is provided a user representation construction apparatus, the apparatus comprising:
the data acquisition module is used for acquiring user data of a user to be imaged, wherein the user data at least comprises basic data and behavior data of the user to be imaged;
the first label module is used for generating a basic label of the user to be imaged according to the user data;
the second label module is used for performing combined calculation on the basic labels through a pre-trained label model to obtain the composite labels of the users to be imaged;
and the first portrait module is used for generating an individual portrait corresponding to the user to be pictured according to the basic label, the composite label and the portrait type of the user to be pictured.
Further, the data acquisition module comprises:
the data analysis unit is used for analyzing logistics information of a user to be imaged in a logistics system to obtain basic data of the user to be imaged;
and the data acquisition unit is used for acquiring the behavior data of the user to be imaged from a third-party data source according to the basic data.
In a third aspect, a computer device is provided, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the computer program, the following steps are implemented:
acquiring user data of a user to be imaged, and generating a basic label of the user to be imaged according to the user data, wherein the user data at least comprises basic data and behavior data of the user to be imaged;
performing combined calculation on the basic labels through a pre-trained label model to generate a composite label of the user to be imaged;
and generating an individual portrait corresponding to the user to be pictured according to the basic label, the composite label and the portrait type of the user to be pictured.
In a fourth aspect, there is provided a computer readable storage medium having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring user data of a user to be imaged, and generating a basic label of the user to be imaged according to the user data, wherein the user data at least comprises basic data and behavior data of the user to be imaged;
performing combined calculation on the basic labels through a pre-trained label model to generate a composite label of the user to be imaged;
and generating an individual portrait corresponding to the user to be pictured according to the basic label, the composite label and the portrait type of the user to be pictured.
The technical scheme provided by the embodiment of the invention has the following beneficial effects:
according to the user portrait construction method and device, the computer equipment and the storage medium, the user data of the user to be pictured are obtained, and the basic label of the user to be pictured is generated according to the user data, wherein the user data at least comprise the basic data and the behavior data of the user to be pictured; performing combined calculation on the basic labels through a pre-trained label model to generate a composite label of the user to be imaged; according to the basic label, the composite label and the portrait type of the user to be pictured, the individual portrait corresponding to the user to be pictured is generated, and the corresponding user portrait is constructed for each application scene, so that the user characteristics can be accurately and quickly identified, accurate service is provided for the user, and the user experience is improved.
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In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a flow diagram illustrating a user representation construction method in accordance with an exemplary embodiment;
FIG. 2 is a schematic diagram illustrating the structure of a user representation construction apparatus in accordance with one illustrative embodiment;
FIG. 3 is a schematic diagram illustrating an internal architecture of a computer device, according to an example embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As described in the background art, as businesses gradually digitize businesses, user (or client, etc.) data becomes more and more huge, and how to recognize the huge user data becomes a problem to be faced by each large-scale business. The currently commonly adopted solution is to construct a user representation for a user, and the user representation constructed by the conventional method is generally a user representation in a narrow sense. The user profile in the narrow sense refers to a tagged model that collects, collates, and analyzes data from the perspective of a user group and abstracts the data according to basic information of the user. The user portrait constructed in this way cannot support different application scenes of each business link. Taking the logistics industry as an example, the application scene can include key customer identification and the like, and the user image constructed by the conventional method is difficult to accurately and quickly identify the characteristics of the customer, so that the key customer cannot be accurately served, the user experience cannot be improved, and the like.
In order to solve the above problems, the embodiment of the present invention creatively provides a user portrait construction method, which generates a basic tag for a user to be pictured according to user data, performs combined calculation on the basic tag by using a pre-trained tag model, generates a composite tag for the user to be pictured, and finally generates an individual portrait corresponding to the user to be pictured according to the basic tag, the composite tag, and a portrait type of the user to be pictured. The user portrait in the implementation of the invention is to portrait the things, mark the user from a plurality of dimensions, and can portrait from the aspects of network points, external fields, products, lines and the like of logistics companies by taking the logistics industry as an example. Through data analysis, corresponding user figures are constructed for each application scene, and user characteristics can be accurately and quickly identified, so that accurate service is provided for users, and user experience is improved.
FIG. 1 is a flow diagram illustrating a user representation construction method, according to an exemplary embodiment, and with reference to FIG. 1, the method includes the steps of:
s1: the method comprises the steps of obtaining user data of a user to be imaged, and generating a basic label of the user to be imaged according to the user data, wherein the user data at least comprise basic data and behavior data of the user to be imaged.
Specifically, in the embodiment of the invention, a label system is systematically built through combing, cleaning and analyzing user data. When the basic tag of the user to be imaged is generated according to the user data, the user data can be calculated by adopting a Hive SQL data processing technology to generate the basic tag. The user data includes, but is not limited to, basic data and behavior data of the user to be represented, where the basic data includes, but is not limited to, user personal information (such as address, telephone, etc.), industry, company job title, economic status, etc., and the behavior data is data related to the user personal behavior, including, but not limited to, personal consumption data, social media data, etc., and is not described herein any more.
In specific implementation, taking the logistics industry as an example, the dimensions of the generated basic tag include, but are not limited to, demographic attributes and behavioral attributes, where the demographic attributes include, but are not limited to, basic user attributes (such as customer name, customer code, industry, division, large area, business department, special industry, company scale, etc.), regional attributes (such as shipping address POI attribute, regular premise, province, urban area, city classification, provincial truck holding capacity, provincial express traffic, provincial part load, etc.), behavioral attributes include, but are not limited to, product demand attributes (such as security sensitivity, whether next day is needed, value-added service is purchased, price sensitivity, etc.), purchase transaction attributes (such as average customer price, payment tool, whether monthly customer is found, most frequent shipping department, etc.), and after-sale service attributes (such as number of damaged products, etc.) The number of claims, the average claim time interval, the average processing time of the claims, the amount of claims required, the amount of actual claims, the degree of damage acceptance, etc.).
S2: and performing combined calculation on the basic labels through a pre-trained label model to generate the composite label of the user to be imaged.
Specifically, in order to enable the constructed user portrait to show user characteristics more clearly, in the embodiment of the invention, besides generating a basic label for the user to be pictured, the generated basic label is also subjected to combined calculation, and a composite label is generated for the user to be pictured.
In specific implementation, a label model is obtained by utilizing pre-prepared training data based on machine learning algorithm training, and then the basic labels obtained in the above steps are combined and calculated by utilizing the label model to obtain corresponding composite labels. The machine learning algorithm includes, but is not limited to, classification, regression, clustering, and other algorithms. As a preferred embodiment, a Python computer library may be used to implement the computation of the composite label.
The dimension of the composite tag can be set according to the actual needs of the user, taking the logistics industry as an example, the dimension of the composite tag includes but is not limited to the user life cycle (such as new users, active users, silent users, lost users, and the like), the customer value (such as high-quality customers, general customers, and the like), the customer classification (clues, opportunities, contracts, goods for walking, and the like), and the description is omitted here.
S3: and generating an individual portrait corresponding to the user to be pictured according to the basic label, the composite label and the portrait type of the user to be pictured.
Specifically, in the actual production process, each service link corresponds to a large number of different service scenes, and in order to improve the accuracy of the generated portrait, in the embodiment of the invention, different portraits are generated aiming at different scenes, such as a salesman portrait, a potential customer portrait, a key customer portrait and the like.
In specific implementation, a mapping relationship can be established in advance for the service scene and the portrait type, and in the corresponding relationship, each portrait type at least corresponds to one service scene. When generating an individual portrait of a user to be portrait, marking a corresponding basic label and a corresponding composite label for the user to be portrait according to the portrait type.
As a preferred implementation manner, in the embodiment of the present invention, the acquiring user data of a user to be imaged includes:
analyzing logistics information of a user to be imaged in a logistics system to obtain basic data of the user to be imaged;
and acquiring the behavior data of the user to be imaged from a third-party data source according to the basic data.
Specifically, in the user portrait construction process in the logistics industry scene, firstly, the logistics information of the user to be pictured is obtained from the logistics system, the logistics information is analyzed, and basic data of the user to be pictured, such as data of a user name, a telephone, a mailing and receiving address and the like, is obtained.
And then, acquiring the behavior data of the user to be imaged from a third-party data source according to scene requirements. The third-party data source includes databases in other different areas of expertise, such as but not limited to APP logs, PC logs, transaction data, third-party data, and the like.
As a preferred implementation manner, in an embodiment of the present invention, the generating an individual portrait corresponding to the user to be pictured according to the base tag, the composite tag, and the portrait type of the user to be pictured includes:
and matching and acquiring a target label corresponding to the portrait type from the basic label and the composite label, and generating the individual portrait of the user to be pictured according to the target label.
Specifically, in the actual production process, each service link corresponds to a large number of different service scenes, and as described above, in order to improve the accuracy of the generated images, in the embodiment of the present invention, different images are generated for different scenes. In specific implementation, a mapping relation is established in advance for the service scene and the portrait type, and in the corresponding relation, each portrait type at least corresponds to one service scene. When generating an individual portrait of a user to be portrait, firstly screening a target label required by a corresponding service scene from a basic label and a composite label according to the portrait type, and then printing the screened target label for the user to be portrait.
As a preferred implementation manner, in an embodiment of the present invention, the method further includes:
and classifying the individual pictures through a pre-trained classification model, the basic labels and the composite labels to generate a group picture corresponding to the user to be pictured.
Specifically, in order to support a business scenario of quickly positioning a target group and the like, such as quickly determining a potential customer group from a large number of users, in the embodiment of the present invention, a group representation may be generated for a user to be represented. The community representation can also display the characteristics of the community from multiple dimensions (such as time, industry, area, product, and the like). In specific implementation, a classification model may also be trained based on a classification algorithm using pre-prepared training data, and then each individual image is classified by using the classification model in combination with the base label and the composite label to generate a corresponding group image.
As a preferred implementation manner, in an embodiment of the present invention, the method further includes:
receiving a first query request sent by a request end, wherein the first query request at least comprises information of a tag to be matched;
and inquiring the individual portrait corresponding to the label information to be matched and returning the individual portrait to the request end.
Specifically, in the embodiment of the invention, the generated user portrait supports query through the tag. When the user portrait is inquired, a first inquiry request which is sent by a request end and carries the information of the tag to be matched is used for inquiring the corresponding individual portrait according to the information of the tag to be matched, and the individual portrait is returned to the request end. The returned individual images can be displayed from multiple label dimensions, the label distribution situation is visually displayed through colors, and operators or data researchers can conveniently and quickly know the characteristics of target users so as to provide basis for follow-up decision making.
As a preferred implementation manner, in an embodiment of the present invention, the method further includes:
receiving a second query request sent by a request end, wherein the second query request at least comprises the individual portrait information to be matched;
and querying the group portrait corresponding to the individual portrait information to be matched and returning the group portrait to the request end.
Specifically, in the embodiment of the invention, the corresponding group is searched for by an individual. In specific implementation, the sent second query request carries the information of the individual portrait to be matched, and then the group portrait corresponding to the information of the individual portrait to be matched is queried and returned to the request end. Similarly, the returned group images can be displayed from multiple label dimensions, so that an operator or a data researcher can intuitively grasp the characteristics of the target group from multiple aspects, and a basis is provided for subsequent decision making.
The user portrait (including individual portrait and group portrait) generated by the user portrait construction method provided by the embodiment of the invention can be applied to a plurality of service scenes, including but not limited to the following:
1. key customer identification
For key customers, service intensity needs to be increased generally, and quality monitoring is performed in the whole process so as to improve customer experience, and therefore it is particularly important to quickly and accurately identify the key customers from massive customer data. By adopting the user portrait construction method provided by the embodiment of the invention, the combination of internal and external data sources is realized, the user portrait based on the label system is established, and after the user portrait is generated, the user portrait can be comprehensively analyzed and judged, so that a key customer group meeting the preset requirements is identified, accurate service is provided for the customer group, the user experience is improved, and the satisfaction is improved.
Specifically, during implementation, a label family and a scoring system of a user portrait of a key customer can be established according to the definition of a business department on the key customer, a data resource of an existing big data platform is utilized, an external data source is combined, the label family of the user portrait is matched with a basic label, a behavior label and the like of the user, a user group is subdivided, a key user customer group is formed, the latest real-time computing (stream computing) technology is continuously updated, orders of the key user group are marked and reminded, quality monitoring service is provided for the whole process of the orders, the demand is responded at the first time, the satisfaction degree is improved, and the viscosity is increased.
When behavior data is acquired from an external data source, the method includes but is not limited to identifying the area and the building where a user is located according to the address of a mail recipient in the basic data of the user to be imaged, providing area information after communicating with real estate data, and enriching related label systems of residence, occupation, income level and the like of the user. In addition, label information can be obtained in databases of other different professional fields according to actual scene requirements.
2. Sales figure
Application scenario and purpose of salesperson portrayal: by extracting and analyzing user tags of a customer group successfully developed by salesmen, sales figures of the customers are generated, and the user tags are traced back to corresponding salesmen, so that the salesmen are helped to distribute clues more conforming to the adequacy, develop more customers, recover attrition customers or maintain the existing high-value customers.
Most customers developed by salespeople accord with the same or similar characteristics, and by analyzing the characteristics of the customers, the customer portrait is established by using the user portrait construction method provided by the embodiment of the invention, and the adequacy attributes of different salespeople are found out. Leads that meet the attributes of the expertise of a certain class of salespersons are then recommended to them, helping to improve the salesperson's developer client efficiency and helping them to recover some attrition clients or maintain existing high value clients.
3. Latent customer representation
Potential customer portrayal application scenarios and objectives: and establishing a user representation of the potential client by performing tagged description on the potential client data. And then, user characteristics which are converted into contract clients are summarized through the user figures of the potential clients, and the probability of converting other potential clients into the contract clients is predicted, so that services can stimulate and maintain the clients more specifically.
FIG. 2 is a schematic diagram of a user representation construction apparatus according to an exemplary embodiment, the apparatus including:
the data acquisition module is used for acquiring user data of a user to be imaged, wherein the user data at least comprises basic data and behavior data of the user to be imaged;
the first label module is used for generating a basic label of the user to be imaged according to the user data;
the second label module is used for performing combined calculation on the basic labels through a pre-trained label model to obtain the composite labels of the users to be imaged;
and the first portrait module is used for generating an individual portrait corresponding to the user to be pictured according to the basic label, the composite label and the portrait type of the user to be pictured.
As a preferred implementation manner, in an embodiment of the present invention, the data obtaining module includes:
the data analysis unit is used for analyzing logistics information of a user to be imaged in a logistics system to obtain basic data of the user to be imaged;
and the data acquisition unit is used for acquiring the behavior data of the user to be imaged from a third-party data source according to the basic data.
As a preferred implementation manner, in an embodiment of the present invention, the first image module is specifically configured to:
and matching and acquiring a target label corresponding to the portrait type from the basic label and the composite label, and generating the individual portrait of the user to be pictured according to the target label.
As a preferred implementation manner, in an embodiment of the present invention, the apparatus further includes:
and the second image module is used for classifying the individual images through a pre-trained classification model, the basic labels and the composite labels to generate group images corresponding to the users to be imaged.
As a preferred implementation manner, in an embodiment of the present invention, the apparatus further includes:
the system comprises a request receiving module, a matching module and a matching module, wherein the request receiving module is used for receiving a first query request sent by a request end, and the first query request at least comprises to-be-matched label information;
and the portrait returning module is used for inquiring the individual portrait corresponding to the tag information to be matched and returning the individual portrait to the request end.
As a preferred implementation manner, in an embodiment of the present invention, the request receiving module is further configured to:
receiving a second query request sent by a request end, wherein the second query request at least comprises the individual portrait information to be matched;
the portrait returning module is also used for inquiring group portraits corresponding to the to-be-matched individual portrait information and returning the group portraits to the request terminal.
Fig. 3 is a schematic diagram illustrating an internal configuration of a computer device according to an exemplary embodiment, which includes a processor, a memory, and a network interface connected through a system bus, as shown in fig. 3. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of optimization of an execution plan.
Those skilled in the art will appreciate that the configuration shown in fig. 3 is a block diagram of only a portion of the configuration associated with aspects of the present invention and is not intended to limit the computing devices to which aspects of the present invention may be applied, and that a particular computing device may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
As a preferred implementation manner, in an embodiment of the present invention, the computer device includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor implements the following steps when executing the computer program:
acquiring user data of a user to be imaged, and generating a basic label of the user to be imaged according to the user data, wherein the user data at least comprises basic data and behavior data of the user to be imaged;
performing combined calculation on the basic labels through a pre-trained label model to generate a composite label of the user to be imaged;
and generating an individual portrait corresponding to the user to be pictured according to the basic label, the composite label and the portrait type of the user to be pictured.
As a preferred implementation manner, in the embodiment of the present invention, when the processor executes the computer program, the following steps are further implemented:
analyzing logistics information of a user to be imaged in a logistics system to obtain basic data of the user to be imaged;
and acquiring the behavior data of the user to be imaged from a third-party data source according to the basic data.
As a preferred implementation manner, in the embodiment of the present invention, when the processor executes the computer program, the following steps are further implemented:
and matching and acquiring a target label corresponding to the portrait type from the basic label and the composite label, and generating the individual portrait of the user to be pictured according to the target label.
As a preferred implementation manner, in the embodiment of the present invention, when the processor executes the computer program, the following steps are further implemented:
and classifying the individual pictures through a pre-trained classification model, the basic labels and the composite labels to generate a group picture corresponding to the user to be pictured.
As a preferred implementation manner, in the embodiment of the present invention, when the processor executes the computer program, the following steps are further implemented:
receiving a first query request sent by a request end, wherein the first query request at least comprises information of a tag to be matched;
and inquiring the individual portrait corresponding to the label information to be matched and returning the individual portrait to the request end.
As a preferred implementation manner, in the embodiment of the present invention, when the processor executes the computer program, the following steps are further implemented:
receiving a second query request sent by a request end, wherein the second query request at least comprises the individual portrait information to be matched;
and querying the group portrait corresponding to the individual portrait information to be matched and returning the group portrait to the request end.
In an embodiment of the present invention, a computer-readable storage medium is further provided, on which a computer program is stored, and when the computer program is executed by a processor, the computer program implements the following steps:
acquiring user data of a user to be imaged, and generating a basic label of the user to be imaged according to the user data, wherein the user data at least comprises basic data and behavior data of the user to be imaged;
performing combined calculation on the basic labels through a pre-trained label model to generate a composite label of the user to be imaged;
and generating an individual portrait corresponding to the user to be pictured according to the basic label, the composite label and the portrait type of the user to be pictured.
As a preferred implementation manner, in the embodiment of the present invention, when executed by the processor, the computer program further implements the following steps:
analyzing logistics information of a user to be imaged in a logistics system to obtain basic data of the user to be imaged;
and acquiring the behavior data of the user to be imaged from a third-party data source according to the basic data.
As a preferred implementation manner, in the embodiment of the present invention, when executed by the processor, the computer program further implements the following steps:
and matching and acquiring a target label corresponding to the portrait type from the basic label and the composite label, and generating the individual portrait of the user to be pictured according to the target label.
As a preferred implementation manner, in the embodiment of the present invention, when executed by the processor, the computer program further implements the following steps:
and classifying the individual pictures through a pre-trained classification model, the basic labels and the composite labels to generate a group picture corresponding to the user to be pictured.
As a preferred implementation manner, in the embodiment of the present invention, when executed by the processor, the computer program further implements the following steps:
receiving a first query request sent by a request end, wherein the first query request at least comprises information of a tag to be matched;
and inquiring the individual portrait corresponding to the label information to be matched and returning the individual portrait to the request end.
As a preferred implementation manner, in the embodiment of the present invention, when executed by the processor, the computer program further implements the following steps:
receiving a second query request sent by a request end, wherein the second query request at least comprises the individual portrait information to be matched;
and querying the group portrait corresponding to the individual portrait information to be matched and returning the group portrait to the request end.
In summary, the technical solution provided by the embodiment of the present invention has the following beneficial effects:
according to the user portrait construction method and device, the computer equipment and the storage medium, the user data of the user to be pictured are obtained, and the basic label of the user to be pictured is generated according to the user data, wherein the user data at least comprise the basic data and the behavior data of the user to be pictured; performing combined calculation on the basic labels through a pre-trained label model to generate a composite label of the user to be imaged; according to the basic label, the composite label and the portrait type of the user to be pictured, the individual portrait corresponding to the user to be pictured is generated, and the corresponding user portrait is constructed for each application scene, so that the user characteristics can be accurately and quickly identified, accurate service is provided for the user, and the user experience is improved.
It should be noted that: in the user portrait building apparatus provided in the above embodiment, when the portrait service is triggered, only the division of the functional modules is illustrated, and in practical applications, the function distribution may be completed by different functional modules according to needs, that is, the internal structure of the apparatus is divided into different functional modules, so as to complete all or part of the functions described above. In addition, the user portrait construction device and the user portrait construction method embodiment provided by the above embodiment belong to the same concept, that is, the device is based on the user portrait construction method, and the specific implementation process thereof is detailed in the method embodiment and is not described herein again.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware, where the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (10)
1. A user portrait construction method, characterized in that the method comprises the following steps:
acquiring user data of a user to be imaged, and generating a basic label of the user to be imaged according to the user data, wherein the user data at least comprises basic data and behavior data of the user to be imaged;
performing combined calculation on the basic labels through a pre-trained label model to generate a composite label of the user to be imaged;
and generating an individual portrait corresponding to the user to be pictured according to the basic label, the composite label and the portrait type of the user to be pictured.
2. A user representation construction method according to claim 1, wherein said obtaining user data of a user to be represented comprises:
analyzing logistics information of a user to be imaged in a logistics system to obtain basic data of the user to be imaged;
and acquiring the behavior data of the user to be imaged from a third-party data source according to the basic data.
3. The user portrait construction method according to claim 1 or 2, wherein the generating of the individual portrait corresponding to the user to be pictured according to the base tag, the composite tag and the portrait type of the user to be pictured comprises:
and matching and acquiring a target label corresponding to the portrait type from the basic label and the composite label, and generating the individual portrait of the user to be pictured according to the target label.
4. A user representation construction method according to claim 1 or 2, further comprising:
and classifying the individual pictures through a pre-trained classification model, the basic labels and the composite labels to generate a group picture corresponding to the user to be pictured.
5. A user representation construction method according to claim 1 or 2, further comprising:
receiving a first query request sent by a request end, wherein the first query request at least comprises information of a tag to be matched;
and inquiring the individual portrait corresponding to the label information to be matched and returning the individual portrait to the request end.
6. A user representation construction method as claimed in claim 4, further comprising:
receiving a second query request sent by a request end, wherein the second query request at least comprises the individual portrait information to be matched;
and querying the group portrait corresponding to the individual portrait information to be matched and returning the group portrait to the request end.
7. A user representation construction apparatus, said apparatus comprising:
the data acquisition module is used for acquiring user data of a user to be imaged, wherein the user data at least comprises basic data and behavior data of the user to be imaged;
the first label module is used for generating a basic label of the user to be imaged according to the user data;
the second label module is used for performing combined calculation on the basic labels through a pre-trained label model to obtain the composite labels of the users to be imaged;
and the first portrait module is used for generating an individual portrait corresponding to the user to be pictured according to the basic label, the composite label and the portrait type of the user to be pictured.
8. The user representation construction apparatus of claim 7 wherein said data acquisition module comprises:
the data analysis unit is used for analyzing logistics information of a user to be imaged in a logistics system to obtain basic data of the user to be imaged;
and the data acquisition unit is used for acquiring the behavior data of the user to be imaged from a third-party data source according to the basic data.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of claims 1 to 6 are implemented when the computer program is executed by the processor.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.
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