CN111915366B - User portrait construction method, device, computer equipment and storage medium - Google Patents
User portrait construction method, device, computer equipment and storage medium Download PDFInfo
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- G—PHYSICS
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- G06Q—INFORMATION 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
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
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- G06F16/9535—Search customisation based on user profiles and personalisation
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
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 portrayed, and generating a basic tag of the user to be portrayed according to the user data, wherein the user data at least comprises basic data and behavior data of the user to be portrayed; combining and calculating the basic labels through a pre-trained label model to generate a composite label of the user to be portrayed; and generating an individual portrait corresponding to the user to be portrait according to the basic label, the composite label and the portrait type of the user to be portrait. According to the method and the device, the corresponding user images are built aiming at all application scenes, so that the user characteristics can be accurately and rapidly identified, accurate services are provided for users, and user experience is improved.
Description
Technical Field
The present invention relates to the field of user portrait technology, and in particular, to a user portrait construction method, apparatus, computer device and storage medium.
Background
User portrayal, also known as user role, is widely used in various fields as an effective tool for outlining target users, contacting user appeal and design direction. We often combine the attributes, behaviors and expectations of the user with the most superficial and life-closest utterances during the actual operation. As a virtual representation of an actual user, the user image is formed in a user character that is not built off the product and market, and the formed user character is required to have a primary audience and target group representing the performance representative product.
With the rapid development of the logistics industry and the gradual business digitization of enterprises, the user data of the logistics system are more and more huge. At present, in the logistics industry, no perfect stereoscopic portrait analysis exists, and currently, the stereoscopic portrait analysis is generally only used for classifying types of terminal couriers, and no more comprehensive and deeper portrait system exists. In the face of huge user data, how to construct corresponding user portraits for each application scene, so that user features can be accurately and rapidly identified, how to provide accurate services for key clients to improve user experience and the like are needed to be solved at present.
Disclosure of Invention
In order to solve the problems in the prior art, the embodiment of the invention provides a user portrait construction method, a device, computer equipment and a storage medium, which are used for solving the problems that in the prior art, a large amount of user data is difficult to accurately and rapidly identify client characteristics, and the user experience cannot be improved due to the fact that accurate service cannot be provided for key clients.
In order to solve one or more of the technical problems, the invention adopts the following technical scheme:
in a first aspect, a user portrait construction method is provided, the method including the steps of:
acquiring user data of a user to be portrayed, and generating a basic tag of the user to be portrayed according to the user data, wherein the user data at least comprises basic data and behavior data of the user to be portrayed;
combining and calculating the basic labels through a pre-trained label model to generate a composite label of the user to be portrayed;
and generating an individual portrait corresponding to the user to be portrait according to the basic label, the composite label and the portrait type of the user to be portrait.
Further, the obtaining the user data of the user to be portrait includes:
analyzing the logistics information of the user to be portrayed in the logistics system to obtain the basic data of the user to be portrayed;
and acquiring behavior data of the user to be portrayed from a third party data source according to the basic data.
Further, the generating an individual portrait corresponding to the user to be portrait according to the basic tag, the composite tag and the portrait type of the user to be portrait 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 portrait according to the target label.
Further, the method further comprises:
and classifying the individual portraits through a pre-trained classification model, the basic label and the composite label to generate group portraits corresponding to the users to be portrayed.
Further, the method further comprises:
receiving a first query request sent by a request end, wherein the first query request at least comprises label information to be matched;
and inquiring the individual portrait corresponding to the label information to be matched and returning to the request terminal.
Further, the method further comprises:
receiving a second query request sent by a request end, wherein the second query request at least comprises individual portrait information to be matched:
and inquiring the group portraits corresponding to the individual portraits information to be matched and returning the group portraits to the request terminal.
In a second aspect, there is provided a user portrayal construction apparatus, the apparatus comprising:
the data acquisition module is used for acquiring user data of the user to be portrayed, wherein the user data at least comprises basic data and behavior data of the user to be portrayed;
the first label module is used for generating a basic label of the user to be portrait according to the user data;
the second label module is used for carrying out combination calculation on the basic labels through a pre-trained label model to obtain the composite labels of the users to be portrait;
and the first portrait module is used for generating an individual portrait corresponding to the user to be portrait according to the basic label, the composite label and the portrait type of the user to be portrait.
Further, the data acquisition module includes:
the data analysis unit is used for analyzing the logistics information of the user to be portrayed in the logistics system and obtaining the basic data of the user to be portrayed;
and the data acquisition unit is used for acquiring the behavior data of the user to be portrayed from a third-party data source according to the basic data.
In a third aspect, there is provided a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of:
acquiring user data of a user to be portrayed, and generating a basic tag of the user to be portrayed according to the user data, wherein the user data at least comprises basic data and behavior data of the user to be portrayed;
combining and calculating the basic labels through a pre-trained label model to generate a composite label of the user to be portrayed;
and generating an individual portrait corresponding to the user to be portrait according to the basic label, the composite label and the portrait type of the user to be portrait.
In a fourth aspect, there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of:
acquiring user data of a user to be portrayed, and generating a basic tag of the user to be portrayed according to the user data, wherein the user data at least comprises basic data and behavior data of the user to be portrayed;
combining and calculating the basic labels through a pre-trained label model to generate a composite label of the user to be portrayed;
and generating an individual portrait corresponding to the user to be portrait according to the basic label, the composite label and the portrait type of the user to be portrait.
The technical scheme provided by the embodiment of the invention has the beneficial effects that:
the user portrait construction method, the device, the computer equipment and the storage medium provided by the embodiment of the invention are used for generating the basic label of the user to be portrait according to the user data by acquiring the user data of the user to be portrait, wherein the user data at least comprises the basic data and the behavior data of the user to be portrait; combining and calculating the basic labels through a pre-trained label model to generate a composite label of the user to be portrayed; according to the basic label, the composite label and the portrait type of the user to be portrayed, individual portraits corresponding to the user to be portrayed are generated, and the user characteristics can be accurately and rapidly identified by constructing corresponding user portraits aiming at each application scene, so that accurate service is provided for the user, and user experience is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart illustrating a user portrait construction method according to an exemplary embodiment;
FIG. 2 is a schematic diagram of a user representation construction apparatus according to an example embodiment;
fig. 3 is a schematic diagram illustrating an internal structure of a computer device according to an exemplary embodiment.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, 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 apparent that the described embodiments are only some embodiments of the present invention, not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As described in the background, as business digitizes gradually, user (or client, etc.) data becomes larger and larger, and how to recognize the huge user data has become a problem that each large business needs to face gradually. The current commonly adopted solution is to construct a user portrait for a user, and the user portrayal constructed by the conventional method is usually a user portrait in a narrow sense. The user portrayal in a narrow sense refers to a tagged model that collects, organizes and analyzes data from the perspective of a user group and is abstracted from the user's basic information. The user portrait thus constructed is not capable of supporting different application scenarios of each business link. Taking the logistics industry as an example, the application scene can comprise key customer identification and the like, and the user image constructed by the conventional method is difficult to accurately and rapidly identify the customer characteristics, so that accurate service cannot be provided for the key customer, and user experience cannot be improved.
In order to solve the problems, the invention provides a user portrait construction method, which comprises the steps of generating basic labels for users to be portrayed according to user data, carrying out combined calculation on the basic labels by utilizing a pre-trained label model, generating composite labels for the users to be portrayed, and finally generating individual portrayal corresponding to the users to be portrayed according to the basic labels, the composite labels and portrait types of the users to be portrayed. The user portrait in the implementation of the invention is to portrait things, mark users from multiple dimensions, and take the logistics industry as an example, portrait from the aspects of the website, the outfield, the product, the circuit and the like of a physical distribution company. Through data analysis, corresponding user images are built for each application scene, and user characteristics can be accurately and rapidly identified, so that accurate service is provided for users, and user experience is improved.
FIG. 1 is a flowchart illustrating a user portrait construction method according to an exemplary embodiment, and with reference to FIG. 1, the method includes the steps of:
s1: and obtaining user data of the user to be portrayed, and generating a basic tag of the user to be portrayed according to the user data, wherein the user data at least comprises basic data and behavior data of the user to be portrayed.
Specifically, in the embodiment of the invention, a label system is systematically constructed through carding, cleaning and analysis of user data. When the basic label of the user to be imaged is generated according to the user data, a Hive SQL data processing technology can be adopted to calculate and process the user data so as to generate the basic label. The user data includes, but is not limited to, basic data of the user to be portrait, wherein the basic data includes, but is not limited to, personal information (such as address, telephone, etc.), information of the located industry, company job, economic status, etc., and the behavior data is data related to personal behavior of the user, including, but not limited to, personal consumption data, social media data, etc., which are not described in detail herein.
In particular embodiments, taking the logistics industry as an example, the dimensions of the generated basic label include, but are not limited to, population attributes and behavior attributes, wherein the population attributes include, but are not limited to, user basic attributes (such as client name, client code, industry, public institution, large area, business department, special industry, company scale, etc.), regional attributes (such as shipping address POI attributes, residence, province, urban area, urban classification, province truck holding capacity, province express delivery traffic, province spare part traffic, etc.), behavior attributes include, but are not limited to, product demand attributes (such as security sensitivity, whether next day is needed, whether additional value added service is purchased, price sensitivity, etc.), purchase transaction attributes (such as average customer price, payment tool, whether customer is paid, most commonly shipping department, etc.), after-sale service attributes (such as breakage number, number of claims, average claims time interval, average claims processing duration, claims amount, actual claims amount, breakage acceptance, etc.).
S2: and carrying out combination calculation on the basic labels through a pre-trained label model to generate the composite labels of the users to be portrayed.
Specifically, in order to enable the constructed user image to clearly show the user characteristics, in the embodiment of the invention, in addition to generating the basic label for the user to be imaged, the generated basic label is subjected to combined calculation to generate the composite label for the user to be imaged.
In specific implementation, training data prepared in advance is utilized to acquire a label model based on machine learning algorithm training, and then the label model is utilized to perform combination calculation on the basic labels acquired in the steps to acquire corresponding composite labels. Among them, machine learning algorithms include, but are not limited to, classification, regression, and clustering algorithms. As a preferred embodiment, the computation of the composite tag may be implemented using a Python computation library.
The dimension of the composite tag may be set according to the actual requirement of the user, taking the logistics industry as an example, the dimension of the composite tag includes, but is not limited to, the life cycle of the user (such as new user, active user, silent user, lost user, etc.), the value of the client (such as high-quality client, general client, etc.), and the classification of the client (clues, opportunities, contracts, shipping, etc.), which are not described in detail herein.
S3: and generating an individual portrait corresponding to the user to be portrait according to the basic label, the composite label and the portrait type of the user to be portrait.
Specifically, in the actual production process, each business link corresponds to a large number of different business scenes, and in order to improve the accuracy of the generated images, in the embodiment of the invention, different images, such as sales person images, potential customer images, key customer images and the like, are generated for different scenes.
In the implementation, a mapping relation can be established in advance for the service scene and the portrait types, and each portrait type at least corresponds to one service scene in the corresponding relation. When generating the individual portrait of the user to be portrait, the user to be portrait is marked with corresponding basic labels and compound labels by combining the portrait type.
In a preferred embodiment of the present invention, the obtaining user data of the user to be portrait includes:
analyzing the logistics information of the user to be portrayed in the logistics system to obtain the basic data of the user to be portrayed;
and acquiring behavior data of the user to be portrayed 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 portrait is obtained from the logistics system, the logistics information is analyzed, and the basic data of the user to be portrait, such as the data of a user name, a telephone, a mail receiving address and the like, are obtained.
And then, according to scene requirements, acquiring behavior data of the user to be portrait from a third party data source. The third party data source comprises databases in different professional fields, such as APP logs, PC logs, transaction data, third party data and the like.
In a preferred embodiment of the present invention, the generating, according to the basic tag, the composite tag, and the portrait type of the user to be portrait, an individual portrait corresponding to the user to be portrait 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 portrait according to the target label.
Specifically, in the actual production process, each business link corresponds to a large number of different business scenes, and in order to improve the accuracy of the generated images, in the embodiment of the invention, different images are generated for different scenes. In the implementation, a mapping relation is established in advance for the service scene and the portrait types, and each portrait type at least corresponds to one service scene in the corresponding relation. When an individual portrait of a user to be portrayed is generated, target labels required by corresponding business scenes are screened from basic labels and composite labels according to the portrait type, and then the screened target labels are marked for the user to be portrayed.
As a preferred implementation manner, in an embodiment of the present invention, the method further includes:
and classifying the individual portraits through a pre-trained classification model, the basic label and the composite label to generate group portraits corresponding to the users to be portrayed.
Specifically, in order to support business scenes such as quick positioning target groups, for example, quick determination of potential customer groups from a large number of users, in the embodiment of the invention, group portraits can be generated for users to be portrayed. The representation of the population may also reveal characteristics of the population from multiple dimensions (e.g., time, industry, area, product, etc.). In the implementation, a classification model can be trained based on a classification algorithm by using the training data prepared in advance, and then each individual image is classified by using the classification model in combination with the basic 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 label information to be matched;
and inquiring the individual portrait corresponding to the label information to be matched and returning to the request terminal.
Specifically, in the embodiment of the invention, the generated user portrait supports inquiry through the tag. When user portrait inquiry is carried out, a corresponding individual portrait is inquired according to the label information to be matched through a first inquiry request which is sent by a request end and carries the label information to be matched, and the individual portrait is returned to the request end. The returned individual portraits can be displayed from a plurality of label dimensions, and label distribution conditions are intuitively displayed through colors, so that operators or data researchers can conveniently and quickly know the characteristics of target users, and the basis is provided for subsequent decisions.
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 individual portrait information to be matched;
and inquiring the group portraits corresponding to the individual portraits information to be matched and returning the group portraits to the request terminal.
Specifically, in the embodiment of the invention, the searching of the corresponding group through the individual is also supported. In the implementation, the 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 terminal. Likewise, the returned group portraits can be displayed from multiple tag dimensions to help operators or data researchers intuitively grasp the characteristics of the target group from multiple aspects and provide basis for subsequent decisions.
The user portraits (including individual portraits and group portraits) generated by the user portraits construction method provided in the embodiments of the invention can be applied to a plurality of business scenarios, including but not limited to the following:
1. key customer identification
For key clients, the service strength is usually increased, and the quality is monitored in the whole process to improve the client experience, so that the quick and accurate identification of the key clients from massive client data is particularly important. 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 comprehensive analysis and judgment can be carried out on each user portrait, the key customer group meeting the preset requirements is identified, the accurate service is provided for the customer group, the user experience is improved, and the satisfaction degree is improved.
In particular, when in implementation, a label family and scoring system of a key customer user figure can be established according to the definition of a business department for the key customer, the data resource of the existing large data platform is utilized, the label family of the user figure is applied to match with the basic label, the behavior label and the like of the user in combination with an external data source, a user group is subdivided, the key user group is formed, the latest real-time computing (stream computing) technology is continuously updated and applied, orders of the key user group are marked and reminded, quality monitoring service is provided for the whole process of the orders, the first time response is required, the satisfaction degree is improved, and the viscosity is increased.
When the behavior data is obtained from an external data source, including but not limited to identifying the region and building where the user is located according to the sender receiving address in the basic data of the user to be portrayed, after the user gets through with the property data, the region information is provided, and the relevant tag systems such as residence, occupation, income level and the like of the user are enriched. In addition, the tag information can be obtained from databases in other different professional fields according to actual scene requirements.
2. Sales person portrait
Application scene and purpose of sales person portrait: the sales figures of the clients are generated by extracting and analyzing the user labels of the client groups successfully developed by the sales personnel, and then the user labels are traced back to the corresponding sales personnel, so that the sales personnel can be helped to distribute clues which are more in line with the good attributes, develop more clients, retrieve lost clients or maintain the existing high-value clients.
Most of clients developed by salespersons accord with the same or similar characteristics, and client portraits are established by analyzing the characteristics of the clients and using the user portrayal construction method provided by the embodiment of the invention to find out the good attributes of different salespersons. Clues meeting the attributes of a certain class of sales personnel's profits are then recommended to them, helping to increase sales personnel's development customer efficiency and helping them to retrieve some lost customers or to maintain existing high value customers.
3. Potential customer portrayal
Potential customer portrait application scenario and purpose: by tagging the potential customer data, a user representation of the potential customer is created. And then, the user characteristics converted into the contract clients are summarized through the potential client user portraits, and the probability of converting other potential clients into the contract clients is predicted, so that the service can more pertinently excite and maintain the clients.
FIG. 2 is a schematic diagram of a user representation construction apparatus according to an exemplary embodiment, the apparatus comprising:
the data acquisition module is used for acquiring user data of the user to be portrayed, wherein the user data at least comprises basic data and behavior data of the user to be portrayed;
the first label module is used for generating a basic label of the user to be portrait according to the user data;
the second label module is used for carrying out combination calculation on the basic labels through a pre-trained label model to obtain the composite labels of the users to be portrait;
and the first portrait module is used for generating an individual portrait corresponding to the user to be portrait according to the basic label, the composite label and the portrait type of the user to be portrait.
As a preferred implementation manner, in an embodiment of the present invention, the data acquisition module includes:
the data analysis unit is used for analyzing the logistics information of the user to be portrayed in the logistics system and obtaining the basic data of the user to be portrayed;
and the data acquisition unit is used for acquiring the behavior data of the user to be portrayed from a third-party data source according to the basic data.
In a preferred 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 portrait according to the target label.
As a preferred implementation manner, in an embodiment of the present invention, the apparatus further includes:
and the second portrait module is used for classifying the individual portraits through a pre-trained classification model, the basic label and the composite label to generate group portraits corresponding to the users to be portrayed.
As a preferred implementation manner, in an embodiment of the present invention, the apparatus further includes:
the request receiving module is used for receiving a first query request sent by a request end, wherein the first query request at least comprises label information to be matched;
and the portrait returning module is used for inquiring the individual portrait corresponding to the label information to be matched and returning the individual portrait to the request terminal.
As a preferred implementation manner, in the 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 individual portrait information to be matched;
the portrait returning module is also used for inquiring the group portrait corresponding to the individual portrait information to be matched and returning the group portrait to the request terminal.
Fig. 3 is a schematic diagram showing an internal structure of a computer device including a processor, a memory, and a network interface connected through a system bus, as shown with reference to fig. 3, according to an exemplary embodiment. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. 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 optimizing an execution plan.
It will be appreciated by those skilled in the art that the structure shown in FIG. 3 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
As a preferred implementation manner, in an embodiment of the present invention, a computer device includes a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the following steps:
acquiring user data of a user to be portrayed, and generating a basic tag of the user to be portrayed according to the user data, wherein the user data at least comprises basic data and behavior data of the user to be portrayed;
combining and calculating the basic labels through a pre-trained label model to generate a composite label of the user to be portrayed;
and generating an individual portrait corresponding to the user to be portrait according to the basic label, the composite label and the portrait type of the user to be portrait.
In a preferred embodiment of the present invention, the processor executes the computer program to further implement the following steps:
analyzing the logistics information of the user to be portrayed in the logistics system to obtain the basic data of the user to be portrayed;
and acquiring behavior data of the user to be portrayed from a third party data source according to the basic data.
In a preferred embodiment of the present invention, the processor executes the computer program to further implement 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 portrait according to the target label.
In a preferred embodiment of the present invention, the processor executes the computer program to further implement the following steps:
and classifying the individual portraits through a pre-trained classification model, the basic label and the composite label to generate group portraits corresponding to the users to be portrayed.
In a preferred embodiment of the present invention, the processor executes the computer program to further implement the following steps:
receiving a first query request sent by a request end, wherein the first query request at least comprises label information to be matched;
and inquiring the individual portrait corresponding to the label information to be matched and returning to the request terminal.
In a preferred embodiment of the present invention, the processor executes the computer program to further implement the following steps:
receiving a second query request sent by a request end, wherein the second query request at least comprises individual portrait information to be matched;
and inquiring the group portraits corresponding to the individual portraits information to be matched and returning the group portraits to the request terminal.
In an embodiment of the present invention, there is also provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of:
acquiring user data of a user to be portrayed, and generating a basic tag of the user to be portrayed according to the user data, wherein the user data at least comprises basic data and behavior data of the user to be portrayed;
combining and calculating the basic labels through a pre-trained label model to generate a composite label of the user to be portrayed;
and generating an individual portrait corresponding to the user to be portrait according to the basic label, the composite label and the portrait type of the user to be portrait.
As a preferred implementation manner, in the embodiment of the present invention, when the computer program is executed by the processor, the following steps are further implemented:
analyzing the logistics information of the user to be portrayed in the logistics system to obtain the basic data of the user to be portrayed;
and acquiring behavior data of the user to be portrayed 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 computer program is executed by the processor, 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 portrait according to the target label.
As a preferred implementation manner, in the embodiment of the present invention, when the computer program is executed by the processor, the following steps are further implemented:
and classifying the individual portraits through a pre-trained classification model, the basic label and the composite label to generate group portraits corresponding to the users to be portrayed.
As a preferred implementation manner, in the embodiment of the present invention, when the computer program is executed by the processor, the following steps are further implemented:
receiving a first query request sent by a request end, wherein the first query request at least comprises label information to be matched;
and inquiring the individual portrait corresponding to the label information to be matched and returning to the request terminal.
As a preferred implementation manner, in the embodiment of the present invention, when the computer program is executed by the processor, the following steps are further implemented:
receiving a second query request sent by a request end, wherein the second query request at least comprises individual portrait information to be matched;
and inquiring the group portraits corresponding to the individual portraits information to be matched and returning the group portraits to the request terminal.
In summary, the technical solution provided by the embodiment of the present invention has the following beneficial effects:
the user portrait construction method, the device, the computer equipment and the storage medium provided by the embodiment of the invention are used for generating the basic label of the user to be portrait according to the user data by acquiring the user data of the user to be portrait, wherein the user data at least comprises the basic data and the behavior data of the user to be portrait; combining and calculating the basic labels through a pre-trained label model to generate a composite label of the user to be portrayed; according to the basic label, the composite label and the portrait type of the user to be portrayed, individual portraits corresponding to the user to be portrayed are generated, and the user characteristics can be accurately and rapidly identified by constructing corresponding user portraits aiming at each application scene, so that accurate service is provided for the user, and user experience is improved.
It should be noted that: the user portrait construction device provided in the above embodiment only uses the division of the above functional modules to illustrate when the portrait service is triggered, in practical application, the above functional allocation may be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the user portrait construction device provided in the above embodiment and the user portrait construction method embodiment belong to the same concept, that is, the device is based on the user portrait construction method, and the specific implementation process of the device is detailed in the method embodiment, which is not described herein.
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 for instructing relevant hardware, where the program may be stored in a computer readable storage medium, and the storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
The foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and scope of the invention are intended to be included within the scope of the invention.
Claims (5)
1. A user portrait construction method is characterized by comprising the following steps:
acquiring user data of a user to be portrayed, and generating a basic tag of the user to be portrayed according to the user data, wherein the user data at least comprises basic data and behavior data of the user to be portrayed; the step of obtaining the user data of the user to be portrayed comprises the steps of analyzing the logistics information of the user to be portrayed in a logistics system, obtaining the basic data of the user to be portrayed, and obtaining the behavior data of the user to be portrayed from a third-party data source according to the basic data;
training and obtaining a label model based on a machine learning algorithm through pre-prepared training data, and carrying out combined calculation on the obtained basic label by utilizing the label model to generate a composite label of the user to be portrayed, wherein the machine learning algorithm comprises classification, regression, clustering and Python calculation library;
matching and acquiring a target label corresponding to the portrait type of the user to be portrayed from the basic label and the composite label, and generating an individual portrait of the user to be portrayed according to the target label;
classifying the individual portraits through a pre-trained classification model, the basic labels and the composite labels to generate group portraits corresponding to the users to be portrayed;
and receiving a second query request sent by a request end, wherein the second query request at least comprises individual portrait information to be matched, and querying a group portrait corresponding to the individual portrait information to be matched and returning the group portrait to the request end.
2. The user portrait construction method according to claim 1, further comprising:
receiving a first query request sent by a request end, wherein the first query request at least comprises label information to be matched;
and inquiring the individual portrait corresponding to the label information to be matched and returning to the request terminal.
3. A user portrayal construction device, said device comprising:
the data acquisition module is used for acquiring user data of the user to be portrayed, wherein the user data at least comprises basic data and behavior data of the user to be portrayed; the data acquisition module comprises a data analysis unit and a data acquisition unit, wherein the data analysis unit is used for analyzing logistics information of a user to be imaged in a logistics system to acquire basic data of the user to be imaged, and the data acquisition unit is used for acquiring behavior data of the user to be imaged from a third-party data source according to the basic data;
the first label module is used for generating a basic label of the user to be portrait according to the user data;
the second label module is used for training and obtaining a label model based on a machine learning algorithm through pre-prepared training data, and carrying out combined calculation on the obtained basic label by utilizing the label model to obtain a composite label of the user to be portrayed, wherein the machine learning algorithm comprises classification, regression, clustering and a Python calculation library;
the first image module is used for matching and acquiring a target label corresponding to the image type of the user to be imaged from the basic label and the composite label, and generating an individual image of the user to be imaged according to the target label;
and the second portrait module is used for classifying the individual portraits through a pre-trained classification model, the basic label and the composite label to generate group portraits corresponding to the users to be portrayed.
4. 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 processor implements the steps of the method of claim 1 or 2 when executing the computer program.
5. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of claim 1 or 2.
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| CN112465565B (en) * | 2020-12-11 | 2023-09-26 | 加和（北京）信息科技有限公司 | User portrait prediction method and device based on machine learning |
| CN113064904B (en) * | 2021-04-29 | 2022-04-08 | 济南慧天云海信息技术有限公司 | Sketch construction method based on data self-learning |
| CN113190731A (en) * | 2021-05-31 | 2021-07-30 | 国家电网有限公司大数据中心 | Label construction method, device, equipment and storage medium |
| CN113807809A (en) * | 2021-08-24 | 2021-12-17 | 姚玲 | Method for constructing audit user portrait based on machine learning technology |
| CN114021175B (en) * | 2021-11-19 | 2022-08-02 | 深圳市电子商务安全证书管理有限公司 | User portrait configuration method and device, computer equipment and medium |
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