CN113282631A - Method and equipment for determining target user based on user portrait data - Google Patents
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Abstract
The method comprises the steps of firstly, generating a logic query program for querying an expected attribute value of each attribute in user portrait data, then, acquiring user portrait description information about a target user, then, determining a logic query program corresponding to the attribute involved in the user portrait description information based on the user portrait description information, and finally, executing the logic query program corresponding to the attribute involved in the user portrait description information based on the user portrait description information and the user portrait data, and determining a user corresponding to the user portrait data matched with the expected attribute value in the user portrait description information as the target user. By the method, developers can develop a user portrait data screening tool with strong universality, user portrayal is not limited, the query requirements of various screening condition combinations are met, and the beneficial effects are brought.
Description
Technical Field
The application relates to the technical field of computer data processing, in particular to a technology for determining a target user based on user portrait data.
Background
In the prior art, user portrait data is generally determined by cleaning the user data through a data platform, tagging each user with a corresponding tag, storing the final data as a wide table, and then filtering user portrait data meeting conditions by using a Structured Query Language (SQL) or the like.
However, in the above-mentioned prior art solution for determining user portrait data, in an actual application scenario, research and development personnel are required to develop different database query tools according to different screening query requirements of an operating user, and the universality is not strong, and especially for the query requirements of various screening condition combinations, the complexity and difficulty of code implementation are also great.
Disclosure of Invention
The application aims to provide a method and equipment for determining a target user based on user portrait data, so as to solve the technical problem of how to determine the target user from the user portrait data simply and quickly in the prior art.
According to one aspect of the application, there is provided a method of determining a target user based on user representation data, wherein the method comprises:
generating a logical query program for querying an expected attribute value of each attribute in the user representation data, wherein the logical query program implements querying of the expected attribute value of each attribute based on query logic corresponding to the expected attribute value of the attribute;
acquiring user portrait description information about a target user, wherein the user portrait description information comprises attributes in user portrait data and expected attribute values corresponding to the attributes;
determining a logical query program corresponding to attributes involved in the user representation description information based on the user representation description information;
executing the logic query program corresponding to the attributes involved in the user representation description information based on the user representation description information and the user representation data, and determining the user corresponding to the user representation data matching the expected attribute values in the user representation description information as the target user.
Optionally, when the user representation data includes a plurality of attributes, there are a plurality of logical query programs, and the method further includes:
packaging the plurality of logical query programs into a logical query program package;
wherein the determining a logical query program corresponding to attributes involved in the user representation description information based on the user representation description information comprises:
calling the logic query program package;
based on the user representation description information, one or more logical query programs corresponding to attributes referenced in the user representation description information are determined from the logical query package.
Optionally, the executing the logical query program corresponding to the attribute involved in the user representation description based on the user representation description information, user representation data, determining that the user corresponding to the user representation data matching the expected attribute value in the user representation description is a target user comprises:
transmitting the user representation description information and user representation data into the logical query package;
executing one or more logical query programs in the logical query package corresponding to the attributes involved in the user representation description information, and determining a user corresponding to user representation data matching the expected attribute values in the user representation description information as a target user.
Optionally, the user portrait description information is presented by means of expressions, where one expression corresponds to presentation of one attribute, and the expression includes an attribute definition part and an expected attribute value part, where the obtaining of the user portrait description information about the target user includes:
acquiring one or more expression presentation information about a target user selected and input by an operating user on an expression editing interface;
generating one or more corresponding expressions based on the one or more expression presentation information;
wherein the determining a logical query program corresponding to attributes involved in the user representation description information based on the user representation description information comprises:
determining attributes involved in the one or more expressions based on the one or more expressions;
determining a logical query program corresponding to attributes involved in the one or more expressions based on the attributes involved.
Optionally, the query logic comprises at least:
acquiring user portrait data;
analyzing the user portrait description information;
the attribute values of the attributes in the user representation data are compared to the desired attribute values in the user representation description information.
Optionally, the method further comprises:
and cleaning the user portrait data based on a preset data format, wherein the preset data format is matched with the data format of the user portrait description information.
Optionally, the logical query package comprises a jar package.
Optionally, when the attribute referred to in the user representation description information includes a plurality of attributes, the executing the logical query program corresponding to the attribute referred to in the user representation description information includes:
a plurality of logical query routines corresponding to the plurality of attributes are executed on each user representation data based on the user representation description information to determine whether the attribute values in the user representation data match the expected attribute values in the user representation description information.
Compared with the prior art, the method and the device for determining the target user based on the user portrait data have the advantages that firstly, a logic query program for querying an expected attribute value of each attribute in the user portrait data is generated, then, user portrait description information about the target user is obtained, then, the logic query program corresponding to the attribute involved in the user portrait description information is determined based on the user portrait description information, finally, the logic query program corresponding to the attribute involved in the user portrait description information is executed based on the user portrait description information and the user portrait data, and the user corresponding to the user portrait data matched with the expected attribute value in the user portrait description information is determined to be the target user. By the method, developers can develop a user portrait data screening tool with strong universality, user portrayal is not limited, the query requirements of various screening condition combinations are met, and the beneficial effects are brought.
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Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments made with reference to the following drawings:
FIG. 1 illustrates a flow diagram of a method for identifying a target user based on user representation data in accordance with an aspect of the subject application;
FIG. 2 illustrates a flow diagram of a method of targeting a user based on user representation data, according to another aspect of the subject application;
FIG. 3 illustrates a block diagram of a system for user representation data targeting, in accordance with another aspect of the subject application;
the same or similar reference numbers in the drawings identify the same or similar elements.
Detailed Description
The present invention is described in further detail below with reference to the attached drawing figures.
In a typical configuration of the present application, each module and trusted party of the system includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include non-transitory computer readable media (transient media), such as modulated data signals and carrier waves.
In order to further explain the technical means and effects adopted by the present application, the following description clearly and completely describes the technical solution of the present application with reference to the accompanying drawings and preferred embodiments.
FIG. 1 illustrates a flow diagram of a method of targeting a user based on user representation data in one aspect of the subject application, wherein the method of one embodiment comprises:
s11, generating a logic query program for querying the expected attribute value of each attribute in the user portrait data, wherein the logic query program realizes the query of the expected attribute value of each attribute based on the query logic corresponding to the expected attribute value of the attribute;
s12, obtaining user portrait description information about a target user, wherein the user portrait description information comprises attributes in the user portrait data and expected attribute values corresponding to the attributes;
s13 determining a logical query program corresponding to the attributes involved in the user representation description information based on the user representation description information;
s14 executes the logic query program corresponding to the attribute involved in the user representation description information based on the user representation description information and user representation data to determine the user corresponding to the user representation data matching the expected attribute value in the user representation description information as the target user.
According to the method, the logic query program is established, the corresponding logic query program is determined based on the obtained user portrait description information of the target user, the target user corresponding to the user portrait description information can be conveniently determined from the user portrait data, user attribute information is not limited, and universality is high.
In the present application, the method is performed by a device 1, the device 1 is a computer device and/or a cloud, the computer device includes but is not limited to a personal computer, a notebook computer, an industrial computer, a network host, a single network server, a plurality of network server sets; the Cloud is made up of a large number of computers or web servers based on Cloud Computing (Cloud Computing), which is a type of distributed Computing, a virtual supercomputer consisting of a collection of loosely coupled computers.
The computer device and/or cloud are merely examples, and other existing or future devices and/or resource sharing platforms, as applicable to the present application, are also intended to be included within the scope of the present application and are hereby incorporated by reference.
In this embodiment, in step S11, a logical query program for querying an expected attribute value of each attribute in the user representation data is generated, where the logical query program implements querying of the expected attribute value of each attribute based on the query logic corresponding to the expected attribute value of the attribute.
The user portrait data is usually stored in a database, where each user portrait data at least includes attributes with different numbers and corresponding attribute values, and the number of the attributes of the user portrait data is different in different application scenarios. For example, in one of the application scenarios, the user representation data of the e-commerce often includes, but is not limited to, attributes such as gender, age, region, membership grade, historical browsing, historical purchasing, consumption amount, consumption date, and the like.
The logic query program for generating the expected attribute value of each attribute in the user portrait data is a logic query program generated for each attribute in the user portrait data, and the expected attribute value of the attribute in the user portrait data can be queried through the logic query program of a certain attribute.
When the user data comprises a plurality of attributes, a plurality of logic query programs are correspondingly generated.
Continuing in this embodiment, in step S12, user representation description information about the target user is obtained, where the user representation description information includes an attribute in the user representation data and an expected attribute value corresponding to the attribute.
The user portrait description information of the target user is determined by the operation user based on actual application requirements, and comprises relevant attributes in the user portrait data and expected attribute values corresponding to the relevant attributes. For example, the operating user needs to acquire a target user of "age greater than 20" in the user image data, wherein the attribute is "age", and the expected attribute value is "greater than 20".
Continuing in this embodiment, in step S13, the determining, based on the user representation description information, a logical query program corresponding to an attribute referenced in the user representation description information.
Optionally, when the user representation data includes a plurality of attributes, there are a plurality of logical query programs, and the method further includes:
packaging the plurality of logical query programs into a logical query program package;
wherein the step S13 includes:
calling the logic query program package;
based on the user representation description information, one or more logical query programs corresponding to attributes referenced in the user representation description information are determined from the logical query package.
Packaging the plurality of logical query programs into a logical query package facilitates increasing an efficiency of determining the logical query program corresponding to the user representation description information.
Continuing in this embodiment, in step S14, the executing of the logical query program corresponding to the attributes referenced in the user representation description based on the user representation description information, user representation data, determines the user corresponding to the user representation data matching the expected attribute values in the user representation description as the target user.
Optionally, the step S14 includes:
transmitting the user representation description information and user representation data into the logical query package;
executing one or more logical query programs in the logical query package corresponding to the attributes involved in the user representation description information, and determining a user corresponding to user representation data matching the expected attribute values in the user representation description information as a target user.
For example, the user needs to identify a target user whose "area is a xu-hui area in shanghai city" and whose age is greater than 20 years "in the user image data, wherein the user image description information includes attributes" area "and" age ", execute two logical query programs corresponding to the attributes" area "and" age "included in the user image description information, and identify a target user whose expected attribute value is" xu-hui area "and" greater than 20 years "from the user image data. Facilitating rapid determination of expected attribute values from user representation data.
Optionally, the user portrait description information is presented by means of expressions, where one expression corresponds to presentation of one attribute, and the expression includes an attribute definition part and an expected attribute value part, where the obtaining of the user portrait description information about the target user includes:
acquiring one or more expression presentation information about a target user selected and input by an operating user on an expression editing interface;
generating one or more corresponding expressions based on the one or more expression presentation information;
wherein the step S13 includes:
determining attributes involved in the one or more expressions based on the one or more expressions;
determining a logical query program corresponding to attributes involved in the one or more expressions based on the attributes involved.
The user portrait description information can be presented in an expression mode, and the user can conveniently and conveniently edit the screening conditions of the target user.
The expression presenting information manner is not limited, and may be, for example, "area | shanghai city > xu hui area", "age | is greater than | 20", or other manners, such as applying to the present application, which should be included in the scope of the present application.
The generation of the expression based on the expression presentation information is not limited, and may be, for example, { "name": age "," expect ": 30", or may be in other expression forms, and is also included in the scope of the present application as applicable. And the query requirement input by the user is convenient to operate.
Optionally, the query logic comprises at least:
acquiring user portrait data;
analyzing the user portrait description information;
the attribute values of the attributes in the user representation data are compared to the desired attribute values in the user representation description information.
In one application scenario, an attribute of user representation data corresponds to a logical query program, user representation description information of a target user is presented through one or more expressions, one or more logical query programs corresponding to the related attribute are determined from a logical query package based on the attribute related in the one or more expressions, the one or more logical query programs are executed, user representation data are obtained, the user representation description information is analyzed, an attribute value of the attribute in the user representation data is compared with a desired attribute value in the user representation description information, and the target user is determined. And the query logic is definite, so that the development of developers is facilitated.
Optionally, as shown in fig. 2, the method further includes:
s21, cleaning the user portrait data based on a preset data format, wherein the preset data format is matched with the data format of the user portrait description information.
User portrait data conforming to a preset data format is obtained, and efficiency of determining a target user based on query requirements can be improved.
Optionally, the logical query package comprises a jar package. The jar package may be invoked across platforms.
Optionally, when the attribute referred to in the user representation description information includes a plurality of attributes, the executing the logical query program corresponding to the attribute referred to in the user representation description information includes:
a plurality of logical query routines corresponding to the plurality of attributes are executed on each user representation data based on the user representation description information to determine whether the attribute values in the user representation data match the expected attribute values in the user representation description information. The method can support the combination of various query requirements input by the operation user, and has better flexibility.
FIG. 3 illustrates a block diagram of a system for user representation data targeting in accordance with another aspect of the subject application, wherein the system of one embodiment comprises:
a MySQL database;
HDFS (Hadoop Distributed File System);
spark stream computing platform;
the device 1 is used for data cleaning and expression analysis.
In an application scenario of the system, a query corresponding to each attribute in user portrait data is defined as an expression class in an abstract mode, and a logic query program is generated by coding logic contained in the expression, wherein the logic query program or the expression class contains logic such as acquisition of a value corresponding to the attribute, analysis of an expected attribute value expression, comparison of the attribute value and the expected attribute value, and the like.
All the logical query programs can be combined into one logical query program package, for example, combined and packaged into one jar package. And uploading the logic query program package or jar package to a Spark stream computing platform.
The user description information of the target user is composed of expressions of one or more attributes, the operation user inputs expected attribute values of the relevant attributes on the expression editing page according to the requirements of the operation user, the display of the relevant attributes on the expression editing page corresponds to the realization of the expressions of the corresponding attributes one by one, the operation user selects the expression of the required attributes through the editing expression page and fills in the expected attribute values, and the system stores the user description information of the target user, which is acquired through the expressions of the attributes, in the MySQL database to be correspondingly used as a task to be executed.
The Spark stream computing platform obtains the task to be executed from the MySQL database and executes the task to be executed, obtains user description information of a target user, obtains user portrait data from the HDFS, constructs a set of data processing workflow by using the jar packet, inputs clean user portrait data obtained by cleaning through a data cleaning module of the equipment 1 and relevant attributes and expected attribute values of the target user analyzed through an expression analysis module of the equipment 1 into the data processing workflow, determines the target user after matching computation is carried out on the clean user portrait data based on the relevant attributes and the expected attribute values of the target user, and stores the determined target user into the HDFS.
According to yet another aspect of the present application, there is also provided a computer readable medium having stored thereon computer readable instructions executable by a processor to implement the foregoing method.
According to yet another aspect of the application, there is also provided a method of determining a target user device based on user representation data, wherein the method comprises:
one or more processors; and
a memory storing computer readable instructions that, when executed, cause the processor to perform operations of the method as previously described.
For example, the computer readable instructions, when executed, cause the one or more processors to: generating a logical query routine for querying expected attribute values for each attribute in the user representation data; acquiring user portrait description information about a target user; determining a logical query program corresponding to attributes involved in the user representation description information based on the user representation description information; executing the logic query program corresponding to the attributes involved in the user representation description information based on the user representation description information and the user representation data, and determining the user corresponding to the user representation data matching the expected attribute values in the user representation description information as the target user.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the apparatus claims may also be implemented by one unit or means in software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.
Claims (10)
1. A method of determining a target user based on user representation data, the method comprising:
generating a logical query program for querying an expected attribute value of each attribute in the user representation data, wherein the logical query program implements querying of the expected attribute value of each attribute based on query logic corresponding to the expected attribute value of the attribute;
acquiring user portrait description information about a target user, wherein the user portrait description information comprises attributes in user portrait data and expected attribute values corresponding to the attributes;
determining a logical query program corresponding to attributes involved in the user representation description information based on the user representation description information;
executing the logic query program corresponding to the attributes involved in the user representation description information based on the user representation description information and the user representation data, and determining the user corresponding to the user representation data matching the expected attribute values in the user representation description information as the target user.
2. The method of claim 1, wherein when the user representation data includes a plurality of attributes, there are a plurality of logical query procedures, the method further comprising:
packaging the plurality of logical query programs into a logical query program package;
wherein the determining a logical query program corresponding to attributes involved in the user representation description information based on the user representation description information comprises:
calling the logic query program package;
based on the user representation description information, one or more logical query programs corresponding to attributes referenced in the user representation description information are determined from the logical query package.
3. The method of claim 2, wherein performing the logical query procedure corresponding to attributes involved in the user representation description based on the user representation description information, user representation data, and determining that a user corresponding to user representation data matching expected attribute values in the user representation description is a target user comprises:
transmitting the user representation description information and user representation data into the logical query package;
executing one or more logical query programs in the logical query package corresponding to the attributes involved in the user representation description information, and determining a user corresponding to user representation data matching the expected attribute values in the user representation description information as a target user.
4. The method of any of claims 1-3, wherein the user representation description information is presented by way of expressions, wherein an expression corresponds to the presentation of an attribute, the expression comprising an attribute definition component and an expected attribute value component, and wherein the obtaining user representation description information about a target user comprises:
acquiring one or more expression presentation information about a target user selected and input by an operating user on an expression editing interface;
generating one or more corresponding expressions based on the one or more expression presentation information;
wherein the determining a logical query program corresponding to attributes involved in the user representation description information based on the user representation description information comprises:
determining attributes involved in the one or more expressions based on the one or more expressions;
determining a logical query program corresponding to attributes involved in the one or more expressions based on the attributes involved.
5. The method according to any of claims 1 to 4, wherein the query logic comprises at least:
acquiring user portrait data;
analyzing the user portrait description information;
the attribute values of the attributes in the user representation data are compared to the desired attribute values in the user representation description information.
6. The method according to any one of claims 1 to 5, further comprising:
and cleaning the user portrait data based on a preset data format, wherein the preset data format is matched with the data format of the user portrait description information.
7. The method of claim 2, wherein the logical query package comprises a jar package.
8. The method of any of claims 1-7, wherein when the attributes involved in the user representation description information include a plurality of attributes, the executing the logical query corresponding to the attributes involved in the user representation description information includes:
executing the plurality of attributes on each user representation data based on the user representation description information corresponds with a plurality of logical query procedures to determine whether attribute values in the user representation data match expected attribute values in the user representation description information.
9. A computer-readable medium comprising, in combination,
stored thereon computer readable instructions executable by a processor to implement the method of any one of claims 1 to 8.
10. An apparatus for determining a target user based on user representation data, the apparatus comprising:
one or more processors; and
a memory storing computer readable instructions that, when executed, cause the processor to perform the operations of the method of any of claims 1 to 8.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115098793A (en) * | 2022-03-30 | 2022-09-23 | 陈应书 | User portrait analysis method and system based on big data |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103729448A (en) * | 2013-12-31 | 2014-04-16 | 深圳市科漫达智能管理科技有限公司 | Method and device for querying data |
| CN106484817A (en) * | 2016-09-26 | 2017-03-08 | 广州致远电子股份有限公司 | A kind of data search method and system |
| CN107545035A (en) * | 2017-07-25 | 2018-01-05 | 无锡天脉聚源传媒科技有限公司 | A kind of information search method and device |
| CN109377253A (en) * | 2018-09-04 | 2019-02-22 | 中国平安人寿保险股份有限公司 | Advertisement placement method, device, terminal and storage medium |
| CN110059106A (en) * | 2019-03-18 | 2019-07-26 | 中科恒运股份有限公司 | Visualized data querying method and system |
-
2020
- 2020-02-20 CN CN202010105367.5A patent/CN113282631A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103729448A (en) * | 2013-12-31 | 2014-04-16 | 深圳市科漫达智能管理科技有限公司 | Method and device for querying data |
| CN106484817A (en) * | 2016-09-26 | 2017-03-08 | 广州致远电子股份有限公司 | A kind of data search method and system |
| CN107545035A (en) * | 2017-07-25 | 2018-01-05 | 无锡天脉聚源传媒科技有限公司 | A kind of information search method and device |
| CN109377253A (en) * | 2018-09-04 | 2019-02-22 | 中国平安人寿保险股份有限公司 | Advertisement placement method, device, terminal and storage medium |
| CN110059106A (en) * | 2019-03-18 | 2019-07-26 | 中科恒运股份有限公司 | Visualized data querying method and system |
Non-Patent Citations (1)
| Title |
|---|
| 匡荣杰: "基于JMS的订单后督***的设计与实现", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115098793A (en) * | 2022-03-30 | 2022-09-23 | 陈应书 | User portrait analysis method and system based on big data |
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