CN113157704B - Hierarchical relationship analysis method, device, equipment and computer readable storage medium - Google Patents
Hierarchical relationship analysis method, device, equipment and computer readable storage medium Download PDFInfo
- Publication number
- CN113157704B CN113157704B CN202110489725.1A CN202110489725A CN113157704B CN 113157704 B CN113157704 B CN 113157704B CN 202110489725 A CN202110489725 A CN 202110489725A CN 113157704 B CN113157704 B CN 113157704B
- Authority
- CN
- China
- Prior art keywords
- information
- data set
- user data
- hierarchical
- hierarchical relationship
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/22—Indexing; Data structures therefor; Storage structures
- G06F16/2228—Indexing structures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
- G06F16/215—Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Databases & Information Systems (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Software Systems (AREA)
- Quality & Reliability (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The disclosure provides a hierarchical relationship analysis method, a hierarchical relationship analysis device, an electronic device and a computer readable storage medium, wherein a user data set is obtained, and the user data set comprises data information of a preset number of users; determining association information between data information in a user data set; and carrying out hierarchical relation analysis on the user data set based on the association information to obtain a hierarchical relation analysis result. According to the method and the device, the user data set can be automatically acquired, the association information among the data information in the user data set is determined, and finally the hierarchical relationship analysis is automatically carried out on the user data set based on the association information, so that the hierarchical relationship analysis result among the users is obtained, manual participation is not needed, accuracy is high, and applicability is good. The hierarchical relationship analysis device, the electronic equipment and the computer readable storage medium provided by the disclosure also solve the corresponding technical problems.
Description
Technical Field
The present disclosure relates to the field of computer application technology, and more particularly, to a hierarchical relationship analysis method, apparatus, device, and computer-readable storage medium.
Background
With the popularization of internet technology and the rapid development of mobile internet and smart phones, communication between users is more convenient, and cross-region and non-contact network communication can be performed.
However, it is difficult to analyze the hierarchical relationship between users manually, so that human resources are consumed greatly, accuracy is low, and applicability is poor.
In view of the above, how to improve the applicability of hierarchical relationship analysis is a problem to be solved by those skilled in the art.
Disclosure of Invention
The present disclosure provides a hierarchical relationship analysis method, which can solve the technical problem of how to improve the applicability of hierarchical relationship analysis to a certain extent. The present disclosure also provides a hierarchical relationship analysis apparatus, device, and computer-readable storage medium.
According to a first aspect of an embodiment of the present disclosure, there is provided a hierarchical relationship analysis method, including:
acquiring a user data set, wherein the user data set comprises data information of a preset number of users;
determining association information between the data information in the user data set;
and carrying out hierarchical relation analysis on the user data set based on the association information to obtain a hierarchical relation analysis result.
Preferably, after the user data set is acquired, before the association information between the data information in the user data set is determined, the method further includes:
cleaning the user data set;
the types of the cleaning processing comprise data deduplication, format conversion, invalid information deletion, data completion, field updating, data searching and replacing, case-to-case conversion and character string splicing.
Preferably, the performing hierarchical relationship analysis on the user data set based on the association information to obtain a hierarchical relationship analysis result includes:
and carrying out hierarchical relation analysis on the user data set based on the association information according to a recursive algorithm to obtain a hierarchical relation analysis result.
Preferably, the type of the association information includes a recommendation relationship;
the hierarchical relationship analysis results include recommended hierarchical analysis results.
Preferably, the type of the association information comprises an information sending relation, and the hierarchical relation analysis result comprises an information interaction hierarchical analysis result.
Preferably, the step of performing hierarchical relationship analysis on the user data set based on the association information, after obtaining a hierarchical relationship analysis result, further includes:
acquiring information indexes to be combined and the combination priority of the information indexes;
and carrying out merging processing on the information corresponding to the information index in the hierarchical relation analysis result according to the merging priority to obtain target information.
Preferably, the step of performing hierarchical relationship analysis on the user data set based on the association information, after obtaining a hierarchical relationship analysis result, further includes:
the hierarchical relation analysis result is exported according to a target export mode;
the types of the target export mode include: printing, picture format export, vector diagram format export, PDF format export, excel format export and san format export.
According to a second aspect of the embodiments of the present disclosure, there is provided a hierarchical relationship analysis apparatus including:
the first acquisition module is used for acquiring a user data set, wherein the user data set comprises data information of a preset number of users;
a first determining module, configured to determine association information between the data information in the user data set;
and the first analysis module is used for carrying out hierarchical relation analysis on the user data set based on the association information to obtain a hierarchical relation analysis result.
According to a third aspect of embodiments of the present disclosure, there is provided an electronic device, comprising:
a memory for storing a computer program;
a processor for implementing the steps of any of the hierarchical relationship analysis methods described above when executing the computer program.
According to a fourth aspect of embodiments of the present disclosure, there is provided a computer readable storage medium having stored therein a computer program which, when executed by a processor, implements the steps of the hierarchical relationship analysis method as described in any one of the above.
The hierarchical relation analysis method provided by the disclosure obtains a user data set, wherein the user data set comprises data information of a preset number of users; determining association information between data information in a user data set; and carrying out hierarchical relation analysis on the user data set based on the association information to obtain a hierarchical relation analysis result. According to the method and the device, the user data set can be automatically acquired, the association information among the data information in the user data set is determined, and finally the hierarchical relationship analysis is automatically carried out on the user data set based on the association information, so that the hierarchical relationship analysis result among the users is obtained, manual participation is not needed, accuracy is high, and applicability is good. The hierarchical relationship analysis device, the electronic equipment and the computer readable storage medium provided by the disclosure also solve the corresponding technical problems.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is apparent that the drawings in the following description are only embodiments of the present disclosure, and other drawings may be obtained according to the provided drawings without inventive effort to those of ordinary skill in the art.
FIG. 1 is a first flow diagram illustrating a hierarchical relationship analysis method in accordance with an exemplary embodiment;
FIG. 2 is a schematic diagram of a recommendation level analysis result;
FIG. 3 is a schematic diagram of the results of hierarchical analysis of information interactions;
FIG. 4 is a second flowchart illustrating a hierarchical relationship analysis method in accordance with an exemplary embodiment;
FIG. 5 is a third flowchart illustrating a hierarchical relationship analysis method in accordance with an exemplary embodiment;
FIG. 6 is a fourth flowchart illustrating a hierarchical relationship analysis method in accordance with an exemplary embodiment;
FIG. 7 is a first schematic diagram of a hierarchical relationship analysis device, according to an example embodiment;
fig. 8 is a block diagram of an electronic device 900, according to an example embodiment.
Detailed Description
The following description of the technical solutions in the embodiments of the present disclosure will be made clearly and completely with reference to the accompanying drawings in the embodiments of the present disclosure, and it is apparent that the described embodiments are only some embodiments of the present disclosure, not all embodiments. Based on the embodiments in this disclosure, all other embodiments that a person of ordinary skill in the art would obtain without making any inventive effort are within the scope of protection of this disclosure.
Referring to fig. 1, fig. 1 is a first flowchart illustrating a hierarchical relationship analysis method according to an exemplary embodiment.
The hierarchical relation analysis method related to the present disclosure may include the following steps:
step S101: and acquiring a user data set, wherein the user data set comprises data information of a preset number of users.
It can be appreciated that, because the hierarchical relationship between the plurality of users needs to be analyzed in the user hierarchical relationship analysis, a user data set including data information of a preset number of users needs to be acquired, where the preset number of values may be determined according to actual needs, and the disclosure is not limited herein specifically, for example, the preset number may be a specific number, or may be a number of users on a certain software or platform, or the like.
It should be noted that the type of the data information of the user may be determined according to actual needs, for example, the data information may be an ID, a name, a mobile phone number, an identification card number, a bank account number, a user level, a registration time, an IP address, and the like of the user.
Step S102: association information between data information in the user data set is determined.
It can be appreciated that the determination of the hierarchical relationship needs to rely on the association relationship between the users, so after the user data set including the data information of the preset number of users is acquired, the association relationship between the data information in the user data set needs to be determined, and the type of the association relationship can be determined according to actual needs.
It should be noted that the type of the association information may be affected by specific information, for example, in the recommendation relationship, for the information 1, it may be that the user a recommends the information 1 to the user B, and for the information 2, there may be a case that the user B recommends the information 2 to the user a, so in a case that the type of the association information affects the association result, the corresponding association information may also be determined according to the type of the association information, etc., which is not particularly limited herein.
Step S103: and carrying out hierarchical relation analysis on the user data set based on the association information to obtain a hierarchical relation analysis result.
It can be understood that after determining the association information between the data information in the user data set, the user data set may be automatically subjected to hierarchical relationship analysis based on the association information to obtain a corresponding hierarchical relationship analysis result, for example, in the case that the type of the association information is a recommendation relationship, the hierarchical relationship analysis result may be a recommendation hierarchical analysis result, which may be shown in fig. 2; in the case where the type of the associated information is an information transmission relationship, the hierarchical relationship analysis result may be an information interaction hierarchical analysis result or the like, for example, if the information transmission relationship is a commodity transmission relationship, the information interaction hierarchical analysis result may be as shown in fig. 3 or the like.
The hierarchical relation analysis method provided by the disclosure obtains a user data set, wherein the user data set comprises data information of a preset number of users; determining association information between data information in a user data set; and carrying out hierarchical relation analysis on the user data set based on the association information to obtain a hierarchical relation analysis result. According to the method and the device, the user data set can be automatically acquired, the association information among the data information in the user data set is determined, and finally the hierarchical relationship analysis is automatically carried out on the user data set based on the association information, so that the hierarchical relationship analysis result among the users is obtained, manual participation is not needed, accuracy is high, and applicability is good.
Referring to fig. 4, fig. 4 is a second flowchart illustrating a hierarchical relationship analysis method according to an exemplary embodiment.
The hierarchical relation analysis method related to the present disclosure may include the following steps:
step S201: and acquiring a user data set, wherein the user data set comprises data information of a preset number of users.
Step S202: cleaning the user data set; the types of the cleaning processing comprise data deduplication, format conversion, invalid information deletion, data completion, field updating, data searching and replacing, case-to-case conversion and character string splicing.
In the present disclosure, after a user data set is acquired and before the associated information between data information in the user data set is determined, in order to quickly perform hierarchical relationship analysis, a cleaning process may be performed on the user data set, and then the cleaned user data set is processed, where a type of the cleaning process includes data deduplication, format conversion, deletion of invalid information, data completion, field update, data search replacement, case conversion, character string concatenation, and the like.
Step S203: association information between data information in the user data set is determined.
Step S204: and carrying out hierarchical relation analysis on the user data set based on the association information to obtain a hierarchical relation analysis result.
In the hierarchical relation analysis method according to the present disclosure, in a process of performing hierarchical relation analysis on a user data set based on association information to obtain a hierarchical relation analysis result, since similarity exists between each hierarchical relation of the user data set, and a recursive algorithm (recursion algorithm) is a method for solving a problem by repeatedly decomposing the problem into similar sub-problems, in order to rapidly obtain the hierarchical relation analysis result, hierarchical relation analysis may be performed on the user data set based on association information according to the recursive algorithm to obtain the hierarchical relation analysis result.
Referring to fig. 5, fig. 5 is a third flowchart illustrating a hierarchical relationship analysis method according to an exemplary embodiment.
The hierarchical relation analysis method related to the present disclosure may include the following steps:
step S301: and acquiring a user data set, wherein the user data set comprises data information of a preset number of users.
Step S302: association information between data information in the user data set is determined.
Step S303: and carrying out hierarchical relation analysis on the user data set based on the association information to obtain a hierarchical relation analysis result.
Step S304: and acquiring the merging priority of the information indexes to be merged.
Step S305: and carrying out merging processing on the information corresponding to the information index in the hierarchical relation analysis result according to the merging priority to obtain target information.
It can be understood that in a specific application scenario, a plurality of accounts may be registered by a single user, so that a situation that a plurality of data information exists by the single user may exist, at this time, in order to track and manage a real user, after performing hierarchical relationship analysis on a user data set based on association information to obtain a hierarchical relationship analysis result, account information of the same user may be combined to obtain user information corresponding to the account, that is, information of a natural person falls to the ground, and specifically, an information index to be combined and a combination priority of the information index may be obtained; and carrying out merging processing on the information corresponding to the information index in the hierarchical relation analysis result according to the merging priority to obtain target information.
It should be noted that the information index and the type of the merge priority can be determined according to actual needs, for example, the information index can be an identification card number, a name, a mobile phone number and a bank card number; the merging priority is: the method comprises the steps of combining data information with the same identity card number into a natural person, combining the data information with the same name and the same mobile phone number into the natural person for the data information with the same identity card number, and combining the data information with the same bank card number into the natural person for the rest data information to obtain final natural person information, namely target information and the like.
Referring to fig. 6, fig. 6 is a fourth flowchart illustrating a hierarchical relationship analysis method according to an exemplary embodiment.
The hierarchical relation analysis method related to the present disclosure may include the following steps:
step S401: and acquiring a user data set, wherein the user data set comprises data information of a preset number of users.
Step S402: association information between data information in the user data set is determined.
Step S403: and carrying out hierarchical relation analysis on the user data set based on the association information to obtain a hierarchical relation analysis result.
Step S404: exporting a hierarchical relation analysis result according to a target export mode; types of target derivation means include: printing, picture format export, vector diagram format export, PDF format export, excel format export and san format export.
It can be understood that in a specific application scenario, due to application requirements, carrying, displaying, analyzing and the like are required to be performed on the hierarchical relationship analysis result, in this process, in order to facilitate processing of the hierarchical relationship analysis result, after the hierarchical relationship analysis is performed on the user data set based on the association information, the hierarchical relationship analysis result can be derived according to a target derivation mode; the types of target derivation means may include: printing, picture format export, vector diagram format export, PDF format export, excel format export, san format export, and the like. It should be noted that the picture format may be jpg, png, bmp or the like.
Referring to fig. 7, fig. 7 is a schematic diagram illustrating a first structure of a hierarchical relationship analysis device according to an exemplary embodiment.
A hierarchical relationship analysis apparatus 700 according to the present disclosure may include:
a first obtaining module 710, configured to obtain a user data set, where the user data set includes data information of a preset number of users;
a first determining module 720, configured to determine association information between data information in the user data set;
the first analysis module 730 is configured to perform hierarchical relationship analysis on the user data set based on the association information, so as to obtain a hierarchical relationship analysis result.
The hierarchical relation analysis device 700 according to the present disclosure may further include:
the first cleaning module is used for cleaning the user data set before the first determining module determines the association information among the data information in the user data set after the first acquiring module acquires the user data set; the types of the cleaning processing comprise data deduplication, format conversion, invalid information deletion, data completion, field updating, data searching and replacing, case-to-case conversion and character string splicing.
The hierarchical relationship analysis device 700 according to the present disclosure, the first analysis module may include:
and the first analysis unit is used for carrying out hierarchical relation analysis on the user data set based on the association information according to a recursive algorithm to obtain a hierarchical relation analysis result.
The hierarchical relationship analysis apparatus 700 according to the present disclosure may include a recommendation relationship;
the hierarchical relationship analysis results may include recommended hierarchical analysis results.
The present disclosure relates to a hierarchical relationship analysis apparatus 700, the type of the associated information may include an information transmission relationship, and the hierarchical relationship analysis result may include an information interaction hierarchical analysis result.
The hierarchical relation analysis device 700 according to the present disclosure may further include:
the second acquisition module is used for carrying out hierarchical relation analysis on the user data set based on the association information by the first analysis module, and acquiring information indexes to be combined and the combination priority of the information indexes after obtaining a hierarchical relation analysis result;
and the first merging module is used for merging the information corresponding to the information index in the hierarchical relation analysis result according to the merging priority to obtain the target information.
The hierarchical relation analysis device 700 according to the present disclosure may further include:
the first deriving module is used for carrying out hierarchical relation analysis on the user data set based on the association information, and deriving the hierarchical relation analysis result according to a target deriving mode after obtaining the hierarchical relation analysis result; types of target derivation means include: printing, picture format export, vector diagram format export, PDF format export, excel format export and san format export.
Fig. 8 is a block diagram of an electronic device 900, according to an example embodiment. As shown in fig. 8, the electronic device 900 may include: processor 901, memory 902. The electronic device 900 may also include one or more of a multimedia component 903, an input/output (I/O) interface 904, and a communication component 905.
The processor 901 is configured to control the overall operation of the electronic device 900 to perform all or part of the steps in the hierarchical relationship analysis method. The memory 902 is used to store various types of data to support operations at the electronic device 900, which may include, for example, instructions for any application or method operating on the electronic device 900, as well as application-related data, such as contact data, transceived messages, pictures, audio, video, and so forth. The Memory 902 may be implemented by any type or combination of volatile or nonvolatile Memory devices, such as static random access Memory (Static Random Access Memory, SRAM for short), electrically erasable programmable Read-Only Memory (Electrically Erasable Programmable Read-Only Memory, EEPROM for short), erasable programmable Read-Only Memory (Erasable Programmable Read-Only Memory, EPROM for short), programmable Read-Only Memory (Programmable Read-Only Memory, PROM for short), read-Only Memory (ROM for short), magnetic Memory, flash Memory, magnetic disk, or optical disk. The multimedia component 903 may include a screen and audio components. Wherein the screen may be, for example, a touch screen, the audio component being for outputting and/or inputting audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may be further stored in the memory 902 or transmitted through the communication component 905. The audio assembly further comprises at least one speaker for outputting audio signals. The I/O interface 904 provides an interface between the processor 901 and other interface modules, which may be a keyboard, mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 905 is used for wired or wireless communication between the electronic device 900 and other devices. Wireless communication, such as Wi-Fi, bluetooth, near field communication (Near Field Communication, NFC for short), 2G, 3G or 4G, or a combination of one or more thereof, the corresponding communication component 905 may thus comprise: wi-Fi module, bluetooth module, NFC module.
In an exemplary embodiment, the electronic device 900 may be implemented by one or more application specific integrated circuits (Application Specific Integrated Circuit, abbreviated ASIC), digital signal processor (Digital Signal Processor, abbreviated DSP), digital signal processing device (Digital Signal Processing Device, abbreviated DSPD), programmable logic device (Programmable Logic Device, abbreviated PLD), field programmable gate array (Field Programmable Gate Array, abbreviated FPGA), controller, microcontroller, microprocessor, or other electronic components for performing the hierarchical relationship analysis method described above.
In another exemplary embodiment, a computer readable storage medium is also provided comprising program instructions which, when executed by a processor, implement the steps of the hierarchical relationship analysis method described above. For example, the computer readable storage medium may be the memory 902 including program instructions described above, which are executable by the processor 901 of the electronic device 900 to perform the hierarchical relationship analysis method described above.
The description of the relevant parts in the hierarchical relationship analysis device, the electronic device and the computer readable storage medium provided in the embodiments of the present disclosure is referred to the detailed description of the corresponding parts in the hierarchical relationship analysis method provided in the embodiments of the present disclosure, and will not be repeated here. In addition, the parts of the foregoing technical solutions provided in the embodiments of the present disclosure, which are consistent with the implementation principles of the corresponding technical solutions in the prior art, are not described in detail, so that redundant descriptions are avoided.
It is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the disclosure. Thus, the present disclosure is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (8)
1. A hierarchical relationship analysis method, comprising:
acquiring a user data set, wherein the user data set comprises data information of a preset number of users;
determining association information between the data information in the user data set;
carrying out hierarchical relation analysis on the user data set based on the association information to obtain a hierarchical relation analysis result;
wherein after the user data set is acquired, before the association information between the data information in the user data set is determined, the method further comprises: cleaning the user data set; the type of the cleaning processing comprises data deduplication, format conversion, invalid information deletion, data completion, field updating, data searching and replacing, case-to-case conversion and character string splicing;
wherein, based on the association information, performing hierarchical relationship analysis on the user data set to obtain a hierarchical relationship analysis result, and then further comprising: acquiring information indexes to be combined and the combination priority of the information indexes; and carrying out merging processing on the information corresponding to the information index in the hierarchical relation analysis result according to the merging priority to obtain target information.
2. The method according to claim 1, wherein the performing hierarchical relationship analysis on the user data set based on the association information to obtain a hierarchical relationship analysis result includes:
and carrying out hierarchical relation analysis on the user data set based on the association information according to a recursive algorithm to obtain a hierarchical relation analysis result.
3. The method of claim 1, wherein the type of association information comprises a recommendation relationship;
the hierarchical relationship analysis results include recommended hierarchical analysis results.
4. The method of claim 1, wherein the type of association information comprises information transmission relationships and the hierarchical relationship analysis results comprise information interaction hierarchical analysis results.
5. The method according to any one of claims 1 to 4, wherein the performing hierarchical relationship analysis on the user data set based on the association information, after obtaining a hierarchical relationship analysis result, further comprises:
the hierarchical relation analysis result is exported according to a target export mode;
the types of the target export mode include: printing, picture format export, vector diagram format export, PDF format export, excel format export and san format export.
6. A hierarchical relationship analysis apparatus, comprising:
the first acquisition module is used for acquiring a user data set, wherein the user data set comprises data information of a preset number of users;
a first determining module, configured to determine association information between the data information in the user data set;
the first analysis module is used for carrying out hierarchical relation analysis on the user data set based on the association information to obtain a hierarchical relation analysis result;
wherein, still include:
the first cleaning module is used for cleaning the user data set before the correlation information among the data information in the user data set is determined after the user data set is acquired by the first acquisition module; the type of the cleaning processing comprises data deduplication, format conversion, invalid information deletion, data completion, field updating, data searching and replacing, case-to-case conversion and character string splicing;
the second acquisition module is used for carrying out hierarchical relation analysis on the user data set based on the association information by the first analysis module, and acquiring information indexes to be combined and the combination priority of the information indexes after obtaining a hierarchical relation analysis result;
and the first merging module is used for merging the information corresponding to the information index in the hierarchical relation analysis result according to the merging priority to obtain target information.
7. An electronic device, comprising:
a memory for storing a computer program;
a processor for implementing the steps of the hierarchical relationship analysis method according to any one of claims 1 to 5 when executing the computer program.
8. A computer readable storage medium, characterized in that the computer readable storage medium has stored therein a computer program which, when executed by a processor, implements the steps of the hierarchical relationship analysis method according to any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110489725.1A CN113157704B (en) | 2021-05-06 | 2021-05-06 | Hierarchical relationship analysis method, device, equipment and computer readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110489725.1A CN113157704B (en) | 2021-05-06 | 2021-05-06 | Hierarchical relationship analysis method, device, equipment and computer readable storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113157704A CN113157704A (en) | 2021-07-23 |
| CN113157704B true CN113157704B (en) | 2023-07-25 |
Family
ID=76873339
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110489725.1A Active CN113157704B (en) | 2021-05-06 | 2021-05-06 | Hierarchical relationship analysis method, device, equipment and computer readable storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113157704B (en) |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8484132B1 (en) * | 2012-06-08 | 2013-07-09 | Lexisnexis Risk Solutions Fl Inc. | Systems and methods for segmented risk scoring of identity fraud |
| CN108536845A (en) * | 2018-04-16 | 2018-09-14 | 中国刑事警察学院 | The incomplete data library file method of inspection |
| CN109446197A (en) * | 2018-09-26 | 2019-03-08 | 深圳壹账通智能科技有限公司 | User information processing method, device, computer equipment and storage medium |
| CN110659395A (en) * | 2019-08-14 | 2020-01-07 | 平安科技（深圳）有限公司 | Relational network map construction method and device, computer equipment and storage medium |
| CN110659799A (en) * | 2019-08-14 | 2020-01-07 | 深圳壹账通智能科技有限公司 | Attribute information processing method and device based on relational network, computer equipment and storage medium |
| CN110738558A (en) * | 2018-07-20 | 2020-01-31 | 京东数字科技控股有限公司 | Information restoration method and device, electronic equipment and computer readable medium |
| CN110781380A (en) * | 2019-09-09 | 2020-02-11 | 深圳壹账通智能科技有限公司 | Information pushing method and device, computer equipment and storage medium |
| CN111274408A (en) * | 2020-01-16 | 2020-06-12 | 广州拉卡拉信息技术有限公司 | Address information verification method and device |
| CN112364035A (en) * | 2021-01-14 | 2021-02-12 | 零犀(北京)科技有限公司 | Processing method and device for call record big data, electronic equipment and storage medium |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130117126A1 (en) * | 2011-11-07 | 2013-05-09 | Apriva, Llc | System and method for secure management of customer data in a loyalty program |
| CN107798068A (en) * | 2017-09-26 | 2018-03-13 | 浙江极赢信息技术有限公司 | A kind of processing method, system and the relevant apparatus of user data of breaking one's promise |
| CN109191334A (en) * | 2018-05-16 | 2019-01-11 | 中国刑事警察学院 | Five heavy duplicate removal multiple level marketing data analysing methods |
| CN109636083A (en) * | 2018-10-16 | 2019-04-16 | 深圳壹账通智能科技有限公司 | Blacklist analysis method, device, equipment and computer readable storage medium |
| CN111506823A (en) * | 2020-03-11 | 2020-08-07 | 平安科技（深圳）有限公司 | Information recommendation method and device and computer equipment |
| CN112100294A (en) * | 2020-09-23 | 2020-12-18 | 杭州安恒信息安全技术有限公司 | User relationship analysis method and device for network platform and related equipment |
| CN112347147A (en) * | 2020-10-28 | 2021-02-09 | 北京奇保信安科技有限公司 | Information pushing method and device based on user association relationship and electronic equipment |
-
2021
- 2021-05-06 CN CN202110489725.1A patent/CN113157704B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8484132B1 (en) * | 2012-06-08 | 2013-07-09 | Lexisnexis Risk Solutions Fl Inc. | Systems and methods for segmented risk scoring of identity fraud |
| CN108536845A (en) * | 2018-04-16 | 2018-09-14 | 中国刑事警察学院 | The incomplete data library file method of inspection |
| CN110738558A (en) * | 2018-07-20 | 2020-01-31 | 京东数字科技控股有限公司 | Information restoration method and device, electronic equipment and computer readable medium |
| CN109446197A (en) * | 2018-09-26 | 2019-03-08 | 深圳壹账通智能科技有限公司 | User information processing method, device, computer equipment and storage medium |
| CN110659395A (en) * | 2019-08-14 | 2020-01-07 | 平安科技（深圳）有限公司 | Relational network map construction method and device, computer equipment and storage medium |
| CN110659799A (en) * | 2019-08-14 | 2020-01-07 | 深圳壹账通智能科技有限公司 | Attribute information processing method and device based on relational network, computer equipment and storage medium |
| CN110781380A (en) * | 2019-09-09 | 2020-02-11 | 深圳壹账通智能科技有限公司 | Information pushing method and device, computer equipment and storage medium |
| CN111274408A (en) * | 2020-01-16 | 2020-06-12 | 广州拉卡拉信息技术有限公司 | Address information verification method and device |
| CN112364035A (en) * | 2021-01-14 | 2021-02-12 | 零犀(北京)科技有限公司 | Processing method and device for call record big data, electronic equipment and storage medium |
Non-Patent Citations (2)
| Title |
|---|
| 基于实体关系的犯罪网络识别机制;周利娟;林鸿飞;罗文华;;计算机应用研究(第03期);第204-208页 * |
| 基于数据挖掘技术的客户关系管理系统研究;宫新军;;山东广播电视大学学报(第01期);第60-63页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113157704A (en) | 2021-07-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111475694B (en) | Data processing method, device, terminal and storage medium | |
| CN110019382B (en) | User intimacy index determination method and device, storage medium and electronic equipment | |
| US20160092441A1 (en) | File Acquiring Method and Device | |
| CN110598109A (en) | Information recommendation method, device, equipment and storage medium | |
| CN112163642A (en) | Wind control rule obtaining method, device, medium and equipment | |
| CN112084179B (en) | Data processing method, device, equipment and storage medium | |
| CN113792212A (en) | Multimedia resource recommendation method, device, equipment and storage medium | |
| CN105187632A (en) | Method and device for determining mobile phone number | |
| CN112784112A (en) | Message checking method and device | |
| CN103812906A (en) | Website recommendation method and device and communication system | |
| CN111666298A (en) | Method and device for detecting user service class based on flink, and computer equipment | |
| CN112966756A (en) | Visual access rule generation method and device, machine readable medium and equipment | |
| CN104090915B (en) | Method and device for updating user data | |
| CN115563377B (en) | Enterprise determination method and device, storage medium and electronic equipment | |
| CN113157704B (en) | Hierarchical relationship analysis method, device, equipment and computer readable storage medium | |
| CN114119123A (en) | Information pushing method and device | |
| CN103064967A (en) | Method and device used for establishing user binary relation bases | |
| CN111078219A (en) | Page display method, device and system, electronic equipment and storage medium | |
| CN113127357B (en) | Unit test method, apparatus, device, storage medium, and program product | |
| CN114298039A (en) | Sensitive word recognition method and device, electronic equipment and storage medium | |
| CN114090738A (en) | Method, device and equipment for determining scene data information and storage medium | |
| CN113674083A (en) | Internet financial platform credit risk monitoring method, device and computer system | |
| CN109634500B (en) | User data filling method and device, terminal equipment and storage medium | |
| CN109274808B (en) | Address book information management method and system, electronic equipment and storage medium | |
| CN111914093A (en) | Data processing method and apparatus, storage medium, and electronic device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |