CN113157704A - Hierarchical relation analysis method, device, equipment and computer readable storage medium - Google Patents
Hierarchical relation analysis method, device, equipment and computer readable storage medium Download PDFInfo
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- 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
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- 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
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- 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
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- 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
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 the associated information among 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. According to the method and the device, the user data set can be automatically obtained, the association information among the data information in the user data set is determined, finally, the hierarchical relation analysis is automatically carried out on the user data set based on the association information, the hierarchical relation analysis result among the users is obtained, manual participation is not needed, the accuracy is high, and the 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 technologies, and in particular, 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 faster, and cross-regional and contactless network communication and the like can be performed.
However, it is difficult to manually analyze the hierarchical relationship between users, the human resource consumption is large, the accuracy is low, and the applicability is poor.
In summary, how to improve the applicability of the hierarchical relationship analysis is a problem to be solved urgently by those skilled in the art.
Disclosure of Invention
The purpose of the present disclosure is to provide 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 disclosure also provides a hierarchical relationship analysis apparatus, a device and a computer readable storage medium.
According to a first aspect of the embodiments 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 the associated information among 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 obtaining the user data set and before the determining the association information between the data information in the user data set, the method further includes:
cleaning the user data set;
the types of the cleaning treatment comprise data duplication removal, format conversion, invalid information deletion, data completion, field updating, data search and replacement, case and 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 associated information according to a recursive algorithm to obtain a hierarchical relation analysis result.
Preferably, the type of the associated information includes a recommendation relationship;
the hierarchical relationship analysis result comprises a recommended hierarchical analysis result.
Preferably, the type of the associated information includes an information sending relationship, and the hierarchical relationship analysis result includes an information interaction hierarchical analysis result.
Preferably, after the analyzing the hierarchical relationship of the user data set based on the association information to obtain a result of the hierarchical relationship analysis, the method further includes:
acquiring information indexes to be combined and the combination priority of the information indexes;
and according to the merging priority, merging the information corresponding to the information index in the hierarchical relationship analysis result to obtain target information.
Preferably, after the analyzing the hierarchical relationship of the user data set based on the association information to obtain a result of the hierarchical relationship analysis, the method further includes:
exporting the hierarchical relationship analysis result according to a target export mode;
the types of the target derivation modes comprise: 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 system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring a user data set, and 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 relationship analysis on the user data set based on the association information to obtain a hierarchical relationship analysis result.
According to a third aspect of the embodiments of the present disclosure, there is provided an electronic apparatus including:
a memory for storing a computer program;
a processor for implementing the steps of the hierarchical relationship analysis method as described above when the computer program is executed.
According to a fourth aspect of the 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 relationship analysis method provided by the present disclosure obtains a user data set, where the user data set includes data information of a preset number of users; determining the associated information among 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. According to the method and the device, the user data set can be automatically obtained, the association information among the data information in the user data set is determined, finally, the hierarchical relation analysis is automatically carried out on the user data set based on the association information, the hierarchical relation analysis result among the users is obtained, manual participation is not needed, the accuracy is high, and the 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 used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present disclosure, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a first flowchart illustrating a hierarchical relationship analysis method in accordance with an exemplary embodiment;
FIG. 2 is a diagram illustrating a recommendation level analysis result;
FIG. 3 is a diagram illustrating the results of a hierarchical analysis of information interaction;
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 block diagram illustrating a hierarchical relationship analysis apparatus in accordance with an exemplary embodiment;
fig. 8 is a block diagram illustrating an electronic device 900 in accordance with an example embodiment.
Detailed Description
The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present 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 by 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 understood that, because the hierarchical relationship among a 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 obtained, a preset number of values may be determined according to actual needs, and the disclosure is not specifically limited herein, for example, the preset number may be a specific value, and may also be a number of users on a certain software or platform, and 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 identity card number, a bank account number, a user rating, registration time, an IP address, and the like of the user.
Step S102: and determining the associated information among the data information in the user data set.
It can be understood that determination of the hierarchical relationship needs to depend on the association relationship among users, so after a user data set including data information of a preset number of users is obtained, the association relationship among the data information in the user data set needs to be determined, the type of the association relationship may be determined according to actual needs, and the disclosure is not specifically limited herein, for example, the association relationship may be a recommendation relationship, an information sending relationship, and the like, the recommendation relationship may recommend a user B for a user a, and the information sending relationship may send information to the user B for the user a.
It should be noted that the type of the associated information may be influenced by specific information, for example, in the recommendation relationship, for information 1, it may be that the user a recommends information 1 to the user B, and for information 2, there may be a case that the user B recommends information 2 to the user a, so that in the case that the type of the associated information influences the association result, corresponding associated information may also be determined according to the type of the associated information, and the disclosure is not limited specifically 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 among the data information in the user data set, the hierarchical relationship analysis may be automatically performed on the user data set based on the association information to obtain a corresponding hierarchical relationship analysis result, for example, in a 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 sending relationship, the hierarchical relationship analysis result may be an information interaction hierarchical analysis result, for example, if the information sending relationship is a commodity sending relationship, the information interaction hierarchical analysis result may be as shown in fig. 3.
The hierarchical relationship analysis method provided by the present disclosure obtains a user data set, where the user data set includes data information of a preset number of users; determining the associated information among 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. According to the method and the device, the user data set can be automatically obtained, the association information among the data information in the user data set is determined, finally, the hierarchical relation analysis is automatically carried out on the user data set based on the association information, the hierarchical relation analysis result among the users is obtained, manual participation is not needed, the accuracy is high, and the 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 by 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 cleaning treatment comprise data duplication removal, format conversion, invalid information deletion, data completion, field updating, data search and replacement, case and case conversion and character string splicing.
In the disclosure, after the user data set is obtained and before the association information between the data information in the user data set is determined, in order to perform hierarchical relationship analysis quickly, the user data set may be cleaned and then the cleaned user data set is processed, where the types of cleaning include data deduplication, format conversion, invalid information deletion, data completion, field update, data search replacement, case conversion, string concatenation, and the like.
Step S203: and determining the associated information among the data information in the user data set.
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 relationship analysis method according to the present disclosure, in a process of analyzing a hierarchical relationship of a user data set based on association information to obtain a hierarchical relationship analysis result, since similarities exist among hierarchical relationships of the user data set, and a recursion algorithm (recursion algorithm) is a method of solving a problem by repeatedly decomposing the problem into similar sub-problems, in order to quickly obtain the hierarchical relationship analysis result, the hierarchical relationship analysis may be performed on the user data set based on the association information according to the recursion algorithm to obtain the hierarchical relationship 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 by 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: and determining the associated information among the data information in the user data set.
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 information indexes to be combined and the combination priority of the information indexes.
Step S305: and according to the merging priority, merging the information corresponding to the information indexes in the hierarchical relationship analysis result to obtain target information.
It can be understood that, in a specific application scenario, a single user may register multiple accounts, so that the single user has multiple data information, at this time, in order to track, supervise and the like a real user, after performing hierarchical relationship analysis on a user data set based on associated information to obtain a hierarchical relationship analysis result, account information of the same user may be merged to obtain user information corresponding to the account, that is, information of a natural person falling to the ground, and specifically, information indexes to be merged and merging priorities of the information indexes may be obtained; and according to the merging priority, merging the information corresponding to the information indexes in the hierarchical relationship analysis result to obtain target information.
It should be noted that the types of the information indexes and the merging priorities may be determined according to actual needs, for example, the information indexes may be identity card numbers, names, mobile phone numbers, and bank card numbers; the merging priority is: the method comprises the steps of firstly merging data information with the same identity card number into a natural person, then merging data information with the same name and the same mobile phone number into the natural person for data information with a blank identity card number, and merging 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 by 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: and determining the associated information among the data information in the user data set.
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; the types of target derivation methods 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, the hierarchical relationship analysis result needs to be carried, displayed, analyzed, and the like, in this process, in order to facilitate processing of the hierarchical relationship analysis result, hierarchical relationship analysis is performed on the user data set based on the association information, and after the hierarchical relationship analysis result is obtained, the hierarchical relationship analysis result can be derived according to a target derivation manner; 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, etc.
Referring to fig. 7, fig. 7 is a first structural diagram of a hierarchical relationship analysis apparatus 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 a 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 to obtain a hierarchical relationship analysis result.
The hierarchical relationship analysis apparatus 700 according to the present disclosure may further include:
the first cleaning module is used for cleaning the user data set after the first acquisition module acquires the user data set and before the first determination module determines the associated information among the data information in the user data set; the types of cleaning treatment comprise data duplication removal, format conversion, invalid information deletion, data completion, field updating, data search and replacement, case and case conversion and character string splicing.
In a hierarchical relationship analysis apparatus 700 according to the present disclosure, a first analysis module may include:
and the first analysis unit is used for carrying out hierarchical relationship analysis on the user data set based on the associated information according to a recursive algorithm to obtain a hierarchical relationship analysis result.
In a hierarchical relationship analysis apparatus 700 according to the present disclosure, the type of the associated information may include a recommendation relationship;
the hierarchical relationship analysis result may include a recommended hierarchical analysis result.
In a hierarchical relationship analysis apparatus 700 according to the present disclosure, 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 relationship analysis apparatus 700 according to the present disclosure may further include:
the second acquisition module is used for the first analysis module to perform hierarchical relationship analysis on the user data set based on the association information to obtain a hierarchical relationship analysis result and then acquire the information indexes to be combined and the combination priority of the information indexes;
and the first merging module is used for merging the information corresponding to the information indexes in the hierarchical relationship analysis result according to the merging priority to obtain the target information.
The hierarchical relationship analysis apparatus 700 according to the present disclosure may further include:
the first derivation module is used for carrying out hierarchical relationship analysis on the user data set based on the association information, and deriving a hierarchical relationship analysis result according to a target derivation mode after the hierarchical relationship analysis result is obtained; the types of target derivation methods 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 illustrating an electronic device 900 in accordance with an example embodiment. As shown in fig. 8, the electronic device 900 may include: a processor 901 and a 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 communications component 905.
The processor 901 is configured to control the overall operation of the electronic device 900, so as to complete 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 operation of the electronic device 900, such as instructions for any application or method operating on the electronic device 900 and application-related data, such as contact data, transmitted and received messages, pictures, audio, video, and the like. The Memory 902 may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk or optical disk. The multimedia component 903 may include a screen and an audio component. Wherein the screen may be, for example, a touch screen and the audio component is used 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 further be stored in the memory 902 or transmitted through the communication component 905. The audio assembly also includes at least one speaker for outputting audio signals. The I/O interface 904 provides an interface between the processor 901 and other interface modules, such as 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 (NFC), 2G, 3G, or 4G, or a combination of one or more of them, so that the corresponding Communication component 905 may include: 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 (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components for performing the hierarchical relationship analysis method described above.
In another exemplary embodiment, there is also provided a computer readable storage medium 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 described above comprising program instructions executable by the processor 901 of the electronic device 900 to perform the hierarchical relationship analysis method described above.
For a description of a relevant part in the hierarchical relationship analysis apparatus, the electronic device, and the computer-readable storage medium provided in the embodiments of the present disclosure, reference is made to the detailed description of the corresponding part in the hierarchical relationship analysis method provided in the embodiments of the present disclosure, and details are not repeated here. In addition, parts of the above technical solutions provided in the embodiments of the present disclosure that are consistent with the implementation principle of the corresponding technical solutions in the prior art are not described in detail, so as to avoid redundant description.
It is further noted that, herein, relational terms such as first and second, and the like may be 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. Also, 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 an … …" does not exclude the presence of other identical 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 (10)
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 the associated information among 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.
2. The method of claim 1, wherein after the obtaining the user data set and before the determining the association information between the data information in the user data set, further comprising:
cleaning the user data set;
the types of the cleaning treatment comprise data duplication removal, format conversion, invalid information deletion, data completion, field updating, data search and replacement, case and case conversion and character string splicing.
3. The method according to claim 1, wherein performing a hierarchical relationship analysis on the user data set based on the association information to obtain a hierarchical relationship analysis result comprises:
and carrying out hierarchical relation analysis on the user data set based on the associated information according to a recursive algorithm to obtain a hierarchical relation analysis result.
4. The method of claim 1, wherein the type of the associated information comprises a recommendation relationship;
the hierarchical relationship analysis result comprises a recommended hierarchical analysis result.
5. The method of claim 1, wherein the type of the associated information comprises an information sending relationship, and the hierarchical relationship analysis result comprises an information interaction hierarchical analysis result.
6. The method according to claim 1, wherein after performing a hierarchical relationship analysis on the user data set based on the association information to obtain a result of the hierarchical relationship analysis, the method further comprises:
acquiring information indexes to be combined and the combination priority of the information indexes;
and according to the merging priority, merging the information corresponding to the information index in the hierarchical relationship analysis result to obtain target information.
7. The method according to any one of claims 1 to 6, wherein after performing a hierarchical relationship analysis on the user data set based on the association information to obtain a hierarchical relationship analysis result, the method further comprises:
exporting the hierarchical relationship analysis result according to a target export mode;
the types of the target derivation modes comprise: printing, picture format export, vector diagram format export, PDF format export, Excel format export and san format export.
8. A hierarchical relationship analysis apparatus, comprising:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring a user data set, and 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 relationship analysis on the user data set based on the association information to obtain a hierarchical relationship analysis result.
9. 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 7 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the hierarchical relationship analysis method according to any one of claims 1 to 7.
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Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130117170A1 (en) * | 2011-11-07 | 2013-05-09 | Apriva, Llc | System and method for secure provision of customer data in a loyalty program |
| US8484132B1 (en) * | 2012-06-08 | 2013-07-09 | Lexisnexis Risk Solutions Fl Inc. | Systems and methods for segmented risk scoring of identity fraud |
| 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 |
| CN108536845A (en) * | 2018-04-16 | 2018-09-14 | 中国刑事警察学院 | The incomplete data library file method of inspection |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
-
2021
- 2021-05-06 CN CN202110489725.1A patent/CN113157704B/en active Active
Patent Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130117170A1 (en) * | 2011-11-07 | 2013-05-09 | Apriva, Llc | System and method for secure provision of customer data in a loyalty program |
| US8484132B1 (en) * | 2012-06-08 | 2013-07-09 | Lexisnexis Risk Solutions Fl Inc. | Systems and methods for segmented risk scoring of identity fraud |
| 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 |
| CN108536845A (en) * | 2018-04-16 | 2018-09-14 | 中国刑事警察学院 | The incomplete data library file method of inspection |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
|---|
| 周利娟;林鸿飞;罗文华;: "基于实体关系的犯罪网络识别机制", 计算机应用研究, no. 03, pages 204 - 208 * |
| 宫新军;: "基于数据挖掘技术的客户关系管理系统研究", 山东广播电视大学学报, no. 01, pages 60 - 63 * |
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