CN117828669A - Method and device for analyzing service data - Google Patents

Method and device for analyzing service data Download PDF

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Publication number
CN117828669A
CN117828669A CN202410010765.7A CN202410010765A CN117828669A CN 117828669 A CN117828669 A CN 117828669A CN 202410010765 A CN202410010765 A CN 202410010765A CN 117828669 A CN117828669 A CN 117828669A
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user
service
information
address information
address
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王泽辉
邵茜
犹锋
朱良姝
赵苗
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China Everbright Bank Co Ltd
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China Everbright Bank Co Ltd
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Priority to CN202410010765.7A priority Critical patent/CN117828669A/en
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/62—Protecting access to data via a platform, e.g. using keys or access control rules
    • G06F21/6218—Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database
    • G06F21/6245—Protecting personal data, e.g. for financial or medical purposes
    • G06F21/6254—Protecting personal data, e.g. for financial or medical purposes by anonymising data, e.g. decorrelating personal data from the owner's identification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • 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
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201—Market modelling; Market analysis; Collecting market data

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  • Health & Medical Sciences (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • Marketing (AREA)
  • Economics (AREA)
  • Game Theory and Decision Science (AREA)
  • Data Mining & Analysis (AREA)
  • Medical Informatics (AREA)
  • Databases & Information Systems (AREA)
  • Computer Hardware Design (AREA)
  • Computer Security & Cryptography (AREA)
  • Software Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The application provides a method for analyzing service data, which comprises the following steps: obtaining user service data flow, wherein the user service data flow comprises user identification information and user service address information, removing address information matched with a preset granularity address in the user address information according to the user identification information and the user service address information to obtain user target service address information, obtaining service site address information, calculating distance information between a user target service address and a service site address according to the service site address information and the user target service address information, and distributing a corresponding preset service strategy according to the distance information and the user identification information. Through the method and the device, when business data analysis is carried out in the financial marketing field, the problem that the corresponding marketing strategy is matched by too many user personal information calculation is solved, data safety and data leakage exist, the data safety can be improved, the data leakage is prevented, and the calculation and network overhead are reduced.

Description

Method and device for analyzing service data
Technical Field
The invention relates to the field of data processing, in particular to a data analysis method and device based on geographic positions.
Background
At present, in the field of financial marketing, when business data is analyzed, excessive user personal information is often required to calculate and match a corresponding marketing strategy, and the problems of data safety and data leakage exist.
In view of the above problems, no effective solution has been proposed at present.
Disclosure of Invention
The embodiment of the invention provides a method for analyzing business data, which at least solves the problems of data safety and data leakage in the related art that excessive user personal information is often needed to calculate and match a corresponding marketing strategy when business data is analyzed in the financial marketing field.
According to an embodiment of the present invention, there is provided a method for analyzing service data, including: acquiring a user service data stream, wherein the user service data stream comprises user identification information and user service address information; removing address information matched with a preset granularity address in the user address information according to the user identification information and the user service address information to obtain user target service address information; acquiring service network address information, and calculating distance information between a user target service address and a service network address according to the service network address information and the user target service address information; and distributing corresponding preset service strategies according to the distance information and the user identification information.
Optionally, the business data stream further includes user business asset information, where the user business asset information includes business asset weight information and business asset registration address information; after obtaining the user target service address information, the method further comprises the following steps: and determining the user frequent address information from the user target service address information according to the service asset weight information and the service asset registration address information.
Optionally, after obtaining the user target service address information, the method further includes: and matching the user target service address information with the service asset registration address information, and eliminating the users with the addresses being empty in the user target service address information.
Optionally, after acquiring the service website address information, the method further includes: and respectively converting the service network point address information and the user frequent address information into longitude and latitude coordinate information.
Optionally, the converting the service website address information and the user constant address information into longitude and latitude coordinate information respectively includes: and calling a map website service interface to respectively convert the business website address information and the user frequent address information into longitude and latitude coordinate information.
Optionally, after converting the service website address information and the user constant address information into longitude and latitude coordinate information respectively, the method further includes: and grouping the longitude and latitude coordinate information of the constant address information of the user according to the preset grouping precision to obtain the longitude and latitude coordinate information of the divided multiple groups of constant address information of the user.
Optionally, the calculating distance information between the user target service address and the service node address according to the service node address information and the user target service address information includes: and calculating the distance information between each group of user frequent address information and the service network address according to the longitude and latitude coordinate information of the service network address information and the longitude and latitude coordinate information of the plurality of groups of frequent address information.
Optionally, the distributing a corresponding preset service policy according to the distance information and the user identification information includes: and distributing corresponding preset service strategies according to the distance information, the user identification information and the user service asset information.
According to another embodiment of the present invention, there is also provided an analysis apparatus for service data, including: the data acquisition module is used for acquiring a user service data stream, wherein the user service data stream comprises user identification information and user service address information; the data processing module is used for removing address information matched with a preset granularity address in the user address information according to the user identification information and the user service address information to obtain user target service address information; the distance calculation module is used for acquiring service network point address information and calculating distance information between a user target service address and a service network point address according to the service network point address information and the user target service address information; and the data analysis module is used for distributing corresponding preset service strategies according to the distance information and the user identification information.
Optionally, the business data stream further includes user business asset information, where the user business asset information includes business asset weight information and business asset registration address information; the apparatus further comprises: and the position calibration module is used for determining the user frequent address information from the user target service address information according to the service asset weight information and the service asset registration address information after the user target service address information is obtained.
Optionally, the location calibration module is further configured to match the user target service address information with the service asset registration address information after obtaining the user target service address information, and reject a user with an address that is empty in the user target service address information.
Optionally, the apparatus further comprises: and the coordinate conversion module is used for respectively converting the service network point address information and the user normal address information into longitude and latitude coordinate information after the service network point address information is acquired.
Optionally, the coordinate conversion module is configured to invoke a map website service interface to convert the business website address information and the user frequent address information into longitude and latitude coordinate information respectively.
Optionally, the distance calculating module is further configured to group the longitude and latitude coordinate information of the normal location address information of the user according to a preset grouping precision after converting the service website address information and the normal location address information of the user into the longitude and latitude coordinate information respectively, so as to obtain the longitude and latitude coordinate information of the divided multiple groups of normal location address information of the user.
Optionally, the distance calculating module is configured to calculate distance information between each group of user frequent address information and the service network address according to the longitude and latitude coordinate information of the service network address information and the longitude and latitude coordinate information of the multiple groups of frequent address information.
Optionally, the data analysis module is configured to allocate a corresponding preset service policy according to the distance information, the user identification information and the user service asset information.
According to a further embodiment of the present invention, there is also provided a computer-readable storage medium having stored therein a computer program, wherein the computer program, when executed by a processor, performs the steps of any of the method embodiments described above.
According to a further embodiment of the invention, there is also provided an electronic device comprising a memory having stored therein a computer program and a processor arranged to run the computer program to perform the steps of any of the method embodiments described above.
According to the invention, the problems of data security and data leakage in the related technology in the financial marketing field, which are caused by the fact that excessive user personal information is often needed to calculate and match the corresponding marketing strategy when business data are analyzed, can be solved. Acquiring a user service data stream, wherein the user service data stream comprises user identification information and user service address information; removing address information matched with a preset granularity address in the user address information according to the user identification information and the user service address information to obtain user target service address information; acquiring service network address information, and calculating distance information between a user target service address and a service network address according to the service network address information and the user target service address information; according to the distance information and the user identification information, corresponding preset service strategies are distributed, so that the safety of data is improved, the data leakage is prevented, and the effects of reducing calculation and network expenses can be achieved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention and together with the description serve to explain the invention and do not constitute a limitation on the invention. In the drawings:
fig. 1 is a block diagram of a hardware structure of a mobile terminal of a method for analyzing service data according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method of analyzing business data according to an embodiment of the invention;
FIG. 3 is a flow chart of a method of analyzing business data according to another embodiment of the present invention;
fig. 4 is a block diagram of a method apparatus for analyzing service data according to an embodiment of the present invention;
fig. 5 is a block diagram of an analysis apparatus of service data according to another embodiment of the present invention.
Detailed Description
The invention will be described in detail hereinafter with reference to the drawings in conjunction with embodiments. It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order.
Example 1
The method embodiment provided in the first embodiment of the present application may be executed in a mobile terminal, a computer terminal or a similar computing device. Taking a mobile terminal as an example, fig. 1 is a block diagram of a hardware structure of a mobile terminal according to an embodiment of the present invention, where, as shown in fig. 1, the mobile terminal may include one or more (only one is shown in fig. 1) processors 102 (the processors 102 may include, but are not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data, and optionally, the mobile terminal may further include a transmission device 106 for a communication function and an input/output device 108. It will be appreciated by those skilled in the art that the structure shown in fig. 1 is merely illustrative and not limiting of the structure of the mobile terminal described above. For example, the mobile terminal may also include more or fewer components than shown in fig. 1, or have a different configuration than shown in fig. 1.
The memory 104 may be used to store a computer program, for example, a software program of application software and a module, such as a computer program corresponding to a method for analyzing service data in an embodiment of the present invention, and the processor 102 executes the computer program stored in the memory 104, thereby performing various functional applications and data processing, that is, implementing the method described above. Memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include memory remotely located relative to the processor 102, which may be connected to the mobile terminal via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission device 106 is used to receive or transmit data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, simply referred to as NIC) that can connect to other network devices through a base station to communicate with the internet. In one example, the transmission device 106 may be a Radio Frequency (RF) module, which is configured to communicate with the internet wirelessly.
In this embodiment, a method for operating on the mobile terminal or the network architecture is provided, fig. 2 is a flowchart of a method for analyzing service data according to an embodiment of the present invention, and as shown in fig. 2, the flowchart includes the following steps:
step S202, obtaining a user service data stream, wherein the user service data stream comprises user identification information and user service address information;
step S204, according to the user identification information and the user service address information, removing address information matched with a preset granularity address in the user address information to obtain user target service address information;
step S206, obtaining service network address information, and calculating the distance information between the user target service address and the service network address according to the service network address information and the user target service address information;
step S208, corresponding preset service strategies are distributed according to the distance information and the user identification information.
Through the steps S202 to S208, the problems of data security and data leakage existing in the case that excessive user personal information is needed to calculate and match the corresponding marketing strategy when the business data is analyzed in the financial marketing field in the related technology can be solved, and the effects of improving the data security, preventing the data leakage and reducing the calculation and network overhead are achieved.
In the embodiment of the invention, the business data stream also comprises user business asset information, wherein the user business asset information comprises business asset weight information and business asset registration address information; after obtaining the user target service address information, the method further comprises the following steps: and determining the user frequent address information from the user target service address information according to the service asset weight information and the service asset registration address information.
In an alternative embodiment, after obtaining the user target service address information, the method further includes: and matching the user target service address information with the service asset registration address information, and eliminating the users with the addresses being empty in the user target service address information.
In another alternative embodiment, after acquiring the service node address information, the method further includes: and respectively converting the service network point address information and the user frequent address information into longitude and latitude coordinate information.
In an optional embodiment, the converting the service website address information and the user holding address information into longitude and latitude coordinate information includes: and calling a map website service interface to respectively convert the business website address information and the user frequent address information into longitude and latitude coordinate information.
In an optional embodiment, after converting the service website address information and the user constant address information into the longitude and latitude coordinate information, the method further includes: and grouping the longitude and latitude coordinate information of the constant address information of the user according to the preset grouping precision to obtain the longitude and latitude coordinate information of the divided multiple groups of constant address information of the user.
In an optional embodiment, the calculating distance information between the user target service address and the service node address according to the service node address information and the user target service address information includes: and calculating the distance information between each group of user frequent address information and the service network address according to the longitude and latitude coordinate information of the service network address information and the longitude and latitude coordinate information of the plurality of groups of frequent address information.
In another optional embodiment, the allocating a corresponding preset service policy according to the distance information and the user identification information includes: and distributing corresponding preset service strategies according to the distance information, the user identification information and the user service asset information.
For example, data of a debit card account opening place, a house place, a credit card account opening place and the like can be acquired from a business system and a commonality data platform which cover business data of a credit card mailing place, a house lending person credit registering place and the like, after data acquisition is completed, user address information in the data is subjected to cleaning, rejecting and the like, address information which is reserved to or is equal to cell granularity is reserved, fine granularity information under cells/roadways/funnels/counseling/courts/villages and the like is rejected, such as cell building, house number, office building floor, village number and the like, and a fuzzy matching mode is adopted to carry out hierarchical filtering cleaning on the user address step by step, and users with empty addresses are rejected.
As one example, user frequent address information may be determined from user business asset weight information and business asset registration address information.
As an example, a map web service interface, such as geocoding and searching for POIs, may be invoked to convert user constant address information and business website address information retained to cell granularity into longitude and latitude coordinate information and store the longitude and latitude coordinate data in a database, such as GaussDB. The longitude and latitude coordinate pairs of each 5000 users can be divided into a group to obtain longitude and latitude coordinate information of the address information of the divided groups of users, linear distances between each group of users and all service network points are calculated in a vector form based on a spherical semi-normal vector formula to obtain a result matrix, the distance matrix of all the groups of users is aggregated, the matrix is resolved into a two-dimensional result table, and the two-dimensional result table is stored in a database, such as GaussDB.
As an example, corresponding preset service policies may be allocated according to the distance information, the user identification information, and the user service asset information according to the time dimension, and the rights may be opened for users in different roles by performing rights management on the user roles in a front-end display part, for example, a front-end screen, a mobile phone billboard, and a display form of a data report.
According to the method and the device, clear and eliminating processing is carried out on data acquired from the user service data flow, user frequent address information is determined according to service asset weight information and service asset registration address information, the service site address information and the user frequent address information are converted into longitude and latitude coordinates and then distance information is calculated, corresponding preset service strategies are distributed according to the distance information, user identification information and the user service asset information, the problem that in the related art, when the service data are analyzed, too much user personal information is often needed to calculate and match the corresponding marketing strategies is solved, the problems of data safety and data leakage exist, and the effects of improving the safety of the data, preventing the data leakage, and reducing calculation and network expenses are achieved.
Fig. 3 is a flowchart of a method for analyzing service data according to another embodiment of the present invention, as shown in fig. 3, the flowchart includes the steps of:
step S301, data is obtained from a user service data stream;
step S302, fine-grained data in the user service data stream is removed;
step S303, determining the usual address information of the user according to the business asset weight information and the business asset registration address information;
step S304, converting business network point address information and user usual address information into longitude and latitude coordinate information respectively;
step S305, calculating the distance information between the user target service address and the service network address;
step S306, corresponding preset business strategies are distributed according to the distance information, the user identification information and the user business asset information.
From the description of the above embodiments, it will be clear to a person skilled in the art that the method according to the above embodiments may be implemented by means of software plus the necessary general hardware platform, but of course also by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk), comprising several instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method described in the embodiments of the present application.
According to another embodiment of the present invention, there is also provided an analysis apparatus of service data, fig. 4 is a block diagram of an analysis apparatus of service data according to an embodiment of the present invention, as shown in fig. 4, including: the device comprises a data acquisition module, a data processing module, a distance calculation module and a data analysis module.
In an optional embodiment, the location calibration module is further configured to match the user target service address information with the service asset registration address information after obtaining the user target service address information, and reject a user with an address that is empty in the user target service address information.
In another alternative embodiment, the apparatus further comprises: and the coordinate conversion module is used for respectively converting the service network point address information and the user normal address information into longitude and latitude coordinate information after the service network point address information is acquired.
In an optional embodiment, the coordinate conversion module is configured to invoke a map website service interface to convert the service website address information and the user usual address information into longitude and latitude coordinate information respectively.
In an optional embodiment, the distance calculating module is further configured to, after converting the service website address information and the user normal location address information into the longitude and latitude coordinate information respectively, group the longitude and latitude coordinate information of the user normal location address information according to a preset grouping precision, and obtain the longitude and latitude coordinate information of the divided multiple groups of user normal location address information.
In an optional embodiment, the distance calculating module is configured to calculate distance information between each group of user frequent address information and the service network address according to the longitude and latitude coordinate information of the service network address information and the longitude and latitude coordinate information of the multiple groups of frequent address information.
In another optional embodiment, the data analysis module is configured to allocate a corresponding preset service policy according to the distance information, the user identification information, and the user service asset information.
In another embodiment, fig. 5 is another block diagram of an apparatus for analyzing service data according to an embodiment of the present invention, as shown in fig. 5, including: the system comprises a user service system, a commonality data platform, a data acquisition module, a data processing module, a position calibration module, a coordinate conversion module, a distance calculation module, a data analysis module, a front-end display module and a support module. The system comprises a data acquisition module, a data processing module, a position calibration module, a coordinate conversion module, a distance calculation module, a data analysis module and other core analysis calculation modules which are deployed on a GaussDB cluster. The front-end display module can comprise a data report, a mobile phone billboard, a front-end screen and the like, and the support module can comprise a power supply, a bus and the like.
It should be noted that each of the above modules may be implemented by software or hardware, and for the latter, it may be implemented by, but not limited to: the modules are all located in the same processor; alternatively, the above modules may be located in different processors in any combination.
Embodiments of the present invention also provide a computer-readable storage medium having a computer program stored therein, wherein the computer program, when executed by a processor, performs the steps of any of the method embodiments described above.
Alternatively, in the present embodiment, the above-described storage medium may be configured to store a computer program for performing the steps of:
s1, acquiring a user service data stream, wherein the user service data stream comprises user identification information and user service address information;
s2, removing address information matched with a preset granularity address in the user address information according to the user identification information and the user service address information to obtain user target service address information;
s3, acquiring service network address information, and calculating distance information between a user target service address and a service network address according to the service network address information and the user target service address information;
s4, distributing corresponding preset service strategies according to the distance information and the user identification information.
Alternatively, in the present embodiment, the storage medium may include, but is not limited to: a usb disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing a computer program.
An embodiment of the invention also provides an electronic device comprising a memory having stored therein a computer program and a processor arranged to run the computer program to perform the steps of any of the method embodiments described above.
Optionally, the electronic apparatus may further include a transmission device and an input/output device, where the transmission device is connected to the processor, and the input/output device is connected to the processor.
Alternatively, in the present embodiment, the above-described processor may be configured to execute the following steps by a computer program:
s1, acquiring a user service data stream, wherein the user service data stream comprises user identification information and user service address information;
s2, removing address information matched with a preset granularity address in the user address information according to the user identification information and the user service address information to obtain user target service address information;
s3, acquiring service network address information, and calculating distance information between a user target service address and a service network address according to the service network address information and the user target service address information;
s4, distributing corresponding preset service strategies according to the distance information and the user identification information.
Alternatively, specific examples in this embodiment may refer to examples described in the foregoing embodiments and optional implementations, and this embodiment is not described herein.
It will be appreciated by those skilled in the art that the modules or steps of the invention described above may be implemented in a general purpose computing device, they may be concentrated on a single computing device, or distributed across a network of computing devices, they may alternatively be implemented in program code executable by computing devices, so that they may be stored in a memory device for execution by computing devices, and in some cases, the steps shown or described may be performed in a different order than that shown or described, or they may be separately fabricated into individual integrated circuit modules, or multiple modules or steps within them may be fabricated into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the principle of the present invention should be included in the protection scope of the present invention.

Claims (11)

1. A method for analyzing service data, comprising:
acquiring a user service data stream, wherein the user service data stream comprises user identification information and user service address information;
removing address information matched with a preset granularity address in the user address information according to the user identification information and the user service address information to obtain user target service address information;
acquiring service network address information, and calculating distance information between a user target service address and a service network address according to the service network address information and the user target service address information;
and distributing corresponding preset service strategies according to the distance information and the user identification information.
2. The method of claim 1, wherein the business data stream further comprises user business asset information, the user business asset information comprising business asset weight information and business asset registration address information; after obtaining the user target service address information, the method further comprises the following steps:
and determining the user frequent address information from the user target service address information according to the service asset weight information and the service asset registration address information.
3. The method of claim 2, further comprising, after obtaining the user target service address information:
and matching the user target service address information with the service asset registration address information, and eliminating the users with the addresses being empty in the user target service address information.
4. The method of claim 2, further comprising, after obtaining the service site address information:
and respectively converting the service network point address information and the user frequent address information into longitude and latitude coordinate information.
5. The method of claim 4, wherein said converting said service site address information and said user constant address information into longitude and latitude coordinate information, respectively, comprises:
and calling a map website service interface to respectively convert the business website address information and the user frequent address information into longitude and latitude coordinate information.
6. The method of claim 4, further comprising, after converting the service site address information and the user constant address information into longitude and latitude coordinate information, respectively:
and grouping the longitude and latitude coordinate information of the constant address information of the user according to the preset grouping precision to obtain the longitude and latitude coordinate information of the divided multiple groups of constant address information of the user.
7. The method of claim 6, wherein said calculating distance information between the user target service address and the service node address based on the service node address information and the user target service address information comprises:
and calculating the distance information between each group of user frequent address information and the service network address according to the longitude and latitude coordinate information of the service network address information and the longitude and latitude coordinate information of the plurality of groups of frequent address information.
8. The method according to claim 2, wherein the allocating a corresponding preset service policy according to the distance information and the user identification information includes:
and distributing corresponding preset service strategies according to the distance information, the user identification information and the user service asset information.
9. An apparatus for analyzing service data, comprising:
the data acquisition module is used for acquiring a user service data stream, wherein the user service data stream comprises user identification information and user service address information;
the data processing module is used for removing address information matched with a preset granularity address in the user address information according to the user identification information and the user service address information to obtain user target service address information;
the distance calculation module is used for acquiring service network point address information and calculating distance information between a user target service address and a service network point address according to the service network point address information and the user target service address information;
and the data analysis module is used for distributing corresponding preset service strategies according to the distance information and the user identification information.
10. A computer-readable storage medium, characterized in that a computer program is stored in the storage medium, wherein the computer program, when being executed by a processor, performs the method of any one of claims 1 to 8.
11. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to run the computer program to perform the method of any of the claims 1 to 8.
CN202410010765.7A 2024-01-02 2024-01-02 Method and device for analyzing service data Pending CN117828669A (en)

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Application Number Priority Date Filing Date Title
CN202410010765.7A CN117828669A (en) 2024-01-02 2024-01-02 Method and device for analyzing service data

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202410010765.7A CN117828669A (en) 2024-01-02 2024-01-02 Method and device for analyzing service data

Publications (1)

Publication Number Publication Date
CN117828669A true CN117828669A (en) 2024-04-05

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Application Number Title Priority Date Filing Date
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Country Status (1)

Country Link
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