CN107704529B

CN107704529B - Information uniqueness identification method, application server, system and storage medium

Info

Publication number: CN107704529B
Application number: CN201710850369.5A
Authority: CN
Inventors: 王恩贵; 项同德; 钱慧敏
Original assignee: Ping An Technology Shenzhen Co Ltd
Current assignee: Ping An Technology Shenzhen Co Ltd
Priority date: 2017-09-20
Filing date: 2017-09-20
Publication date: 2020-04-10
Anticipated expiration: 2037-09-20
Also published as: WO2019056750A1; CN107704529A

Abstract

The invention discloses an information uniqueness identification method, an application server, a system and a storage medium, wherein the information uniqueness identification method acquires basic information of group clients stored in each source database, and the basic information comprises client names and identification information; marking each group client as an accurate identification class or a fuzzy identification class according to the identification information; respectively carrying out accurate identification and fuzzy identification on the group clients in the accurate identification class and the fuzzy identification class according to a preset identification rule, and identifying the group clients which are the same client; and acquiring identification results of accurate identification and fuzzy identification, and integrating basic information of all group customers who are the same customer to obtain the group customer information of unique identification according to the identification results. Accurate identification or fuzzy identification is respectively carried out according to the types of the clients in different groups, and the problem that uniqueness identification and data integration cannot be carried out due to incomplete client information is solved.

Description

Information uniqueness identification method, application server, system and storage medium

Technical Field

The invention relates to the technical field of information identification, in particular to an information uniqueness identification method, an application server, an information uniqueness identification system and a storage medium.

Background

At present, because the number of group clients of a plurality of companies is huge, the group clients need to be identified and data integration so as to be convenient for the management of the group clients, the traditional information uniqueness identification is mainly identified through organizational structure codes of the clients, the identification method is rigorous and accurate, but because the client information is likely to have partial loss and other situations, the information saturation of the organizational structure codes is not high, the accurate identification through the organizational structure codes can cause the incomplete identification and integration of partial information of the clients, and the range of the uniqueness identification of the group clients is limited.

Accordingly, the prior art is yet to be improved and developed.

Disclosure of Invention

In view of the above-mentioned shortcomings in the prior art, an object of the present invention is to provide an information uniqueness recognition method, an application server, a system and a storage medium, which can perform accurate recognition or fuzzy recognition according to the types of clients in different groups, and solve the problem that some clients in different groups cannot perform uniqueness recognition and data integration due to incomplete client information.

In order to achieve the purpose, the invention adopts the following technical scheme:

an information uniqueness identification method, comprising the following steps:

acquiring basic information of group clients stored in each source database, wherein the basic information comprises client names and identification information;

marking each group client as an accurate identification class or a fuzzy identification class according to the identification information;

respectively carrying out accurate identification and fuzzy identification on the group clients in the accurate identification class and the fuzzy identification class according to a preset identification rule, and identifying the group clients which are the same client;

and acquiring identification results of accurate identification and fuzzy identification, and integrating basic information of the group clients according to the identification results to obtain the group client information of unique identification.

In the information uniqueness identification method, the step of marking each group client as a precise identification class or a fuzzy identification class according to the identification information includes:

analyzing the identification information of each group client;

judging whether the identification information of each group client contains preset accurate identification information or not, and if so, marking the identification information as an accurate identification class; otherwise, the label is a fuzzy recognition class.

In the information uniqueness identification method, the group clients in the precise identification class and the fuzzy identification class are respectively precisely identified and fuzzy identified according to a preset identification rule, and the step of identifying the group clients which are the same clients comprises the following steps:

carrying out character detection on the client names of all group clients to acquire the word number and the character content of the client names;

performing unique identification according to preset accurate identification information and a client name of each group client in an accurate identification class, and identifying group clients which are the same client in the accurate identification class;

and performing unique identification according to the identification information of each group client in the fuzzy identification class, the word number and the character content of the client name, and identifying the group clients which are the same client in the fuzzy identification class.

In the information uniqueness identification method, the uniqueness identification is carried out according to the preset accurate identification information and the client name of each group client in the accurate identification class, and the step of identifying the group clients which are the same client in the accurate identification class comprises the following steps:

randomly selecting one group client in the accurate identification class, and comparing the preset accurate identification information and the client name of the group client with the preset accurate identification information and the client name of other group clients in the accurate identification class;

judging whether group clients with the same preset accurate identification information and the same client name exist according to the comparison result, and if so, identifying the group clients with the same preset accurate identification information and the same client name as the selected group clients as the same clients; if not, identifying the selected group client and other group clients in the accurate identification class as different clients;

and continuously selecting another group client in the precise identification class to perform unique identification with other group clients until all the group clients in the precise identification class are identified.

In the information uniqueness identification method, the uniqueness identification is carried out according to the identification information of each group client in the fuzzy identification, the word number and the character content of the client name, and the step of identifying the group clients which are the same clients in the fuzzy identification comprises the following steps:

judging whether the number of the client name words of each group client in the fuzzy identification class is greater than or equal to a preset threshold value or not;

if the number of the words is larger than or equal to the preset threshold value, carrying out unique identification according to the word number and the character content of the client name of the group client;

if the number of the group clients is smaller than the preset threshold value, the unique identification is carried out according to the identification information of the group clients, the word number of the client names and the character content.

In the information uniqueness recognition method, if the number of words and the text content of the customer name of the group customer is greater than or equal to a preset threshold, the step of performing uniqueness recognition according to the word number and the text content of the customer name of the group customer includes:

randomly selecting a group client with the number of the client name words in the fuzzy recognition class being more than or equal to a preset threshold value, and comparing the client name with the client names of all the group clients in a text content manner;

judging whether a group client with the identical text content of the client name exists according to the comparison result, and if so, identifying the group client with the identical text content and the selected group client as the same client; if not, identifying the selected group client and all other group clients as different clients;

and continuously selecting another group client with the client name word number larger than or equal to the preset threshold value in the fuzzy identification to perform unique identification until all the group clients with the client name word number larger than or equal to the preset threshold value in the fuzzy identification are identified.

In the information uniqueness identification method, if the number of the group clients is smaller than the preset threshold, the step of performing uniqueness identification according to the identification information of the group clients, the word number of the client name and the character content comprises the following steps:

randomly selecting a group client with the client name number smaller than a preset threshold in the fuzzy recognition class, and comparing the client name with the client names of all the group clients in terms of text content;

judging whether a group client with the identical character content of the client name exists according to the comparison result, if so, continuously judging whether the group client with the identical character content and the selected group client have any identical identification information, and identifying the group client with the identical character content and any identical identification information and the selected group client as the same client; if not, identifying the selected group client and all other group clients as different clients;

and continuously selecting another group client with the client name word number smaller than the preset threshold value in the fuzzy identification to perform uniqueness identification until all the group clients with the client name word number smaller than the preset threshold value in the fuzzy identification are identified.

An information uniquely identified application server, comprising: a processor, a memory, and a communication bus;

the memory has stored thereon a computer readable program executable by the processor;

the communication bus realizes connection communication between the processor and the memory;

the processor, when executing the computer readable program, implements the steps in the information uniqueness identifying method as described above.

A computer readable storage medium storing one or more programs, the one or more programs being executable by one or more processors to implement the steps in the information uniqueness identifying method as described above.

An information uniqueness identification system comprises a plurality of source databases and also comprises an application server for information uniqueness identification as described above;

each source database is used for storing basic information of the group clients;

the application server is used for acquiring basic information of the group clients stored in each source database, wherein the basic information comprises client names and identification information; marking each group client as an accurate identification class or a fuzzy identification class according to the identification information; respectively carrying out accurate identification and fuzzy identification on the group clients in the accurate identification class and the fuzzy identification class according to a preset identification rule, and identifying the group clients which are the same client; and acquiring identification results of accurate identification and fuzzy identification, and integrating basic information of all group customers who are the same customer to obtain the group customer information of unique identification according to the identification results.

Compared with the prior art, the information uniqueness identification method, the application server, the system and the storage medium provided by the invention have the advantages that the basic information of the group clients stored in each source database is obtained, wherein the basic information comprises the client name and the identification information; then marking each group client as an accurate identification class or a fuzzy identification class according to the identification information; then, according to a preset identification rule, group clients in the accurate identification class and the fuzzy identification class are respectively subjected to accurate identification and fuzzy identification, and the group clients which are the same client are identified; and then acquiring identification results of accurate identification and fuzzy identification, and integrating basic information of all group customers who are the same customer to obtain the group customer information of unique identification according to the identification results. Accurate identification or fuzzy identification can be respectively carried out according to the types of different group customers, and the problem that part of group customers cannot carry out uniqueness identification and data integration due to incomplete customer information is solved.

Drawings

FIG. 1 is a schematic diagram of an application environment of a method for identifying uniqueness of information provided by the present invention;

FIG. 2 is a flow chart of a method for identifying uniqueness of information provided by the present invention;

fig. 3 is a flowchart of step S20 in the information uniqueness identifying method provided by the invention;

fig. 4 is a flowchart of step S30 in the information uniqueness identifying method provided by the invention;

fig. 5 is a flowchart of step S32 in the information uniqueness identifying method provided by the invention;

fig. 6 is a flowchart of step S33 in the information uniqueness identifying method provided by the invention;

fig. 7 is a flowchart of step S332 in the information uniqueness identifying method provided by the present invention;

fig. 8 is a flowchart of step S333 in the information uniqueness identifying method provided by the present invention;

FIG. 9 is a diagram illustrating an operating environment of a unique identifier program according to an embodiment of the present invention;

FIG. 10 is a functional block diagram of a preferred embodiment of an application server for installing a unique identifier for information according to the present invention;

fig. 11 is a block diagram of the information uniqueness recognition system provided by the present invention.

Detailed Description

In view of the defects that uniqueness identification and integration cannot be performed when client information is incomplete in the prior art, the invention aims to provide an information uniqueness identification method, an application server, a system and a storage medium, which can perform accurate identification or fuzzy identification according to types of clients in different groups respectively and solve the problem that a part of group clients cannot perform uniqueness identification and data integration due to incomplete client information.

In order to make the objects, technical solutions and effects of the present invention clearer and clearer, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

Please refer to fig. 1, which is a schematic diagram of an application environment of the information uniqueness recognition method according to the present invention. In the figure, one or more application programs may be installed in the application server to process the relevant data. In this embodiment, the application server may receive the basic information from the group clients stored in each source database, and the application server marks each group client as an accurate identification class or a fuzzy identification class according to the basic information, performs accurate identification and fuzzy identification on the group clients in the accurate identification class and the fuzzy identification class, identifies the group clients that are the same client, and integrates the basic information of the group clients according to the identification result, thereby implementing accurate identification or fuzzy identification according to the types of different group clients, and avoiding the situation that the client information is incomplete and cannot be identified.

Referring to fig. 2, the information uniqueness identifying method provided by the present invention includes the following steps:

and S10, acquiring basic information of the community clients stored in the source databases, wherein the basic information comprises client names and identification information.

In this embodiment, a plurality of source databases may be set to store group client data of different industry companies, and since one group client may have business with different industry companies under the same company, and thus data of the group client is stored in different source databases, it is necessary to perform unique identification and integration on the group clients in all the source databases to facilitate management and data analysis of the group client, specifically, the stored basic information of the group client is obtained from each source database of the different industry companies, where the basic information includes a client name and identification information, and the identification information is information that can identify the identity of the group client, such as an organization code, a business registration number, a tax registration number, a business license number, and the like.

Preferably, the source database is an Oracle database (the Oracle database is also called Oracle RDBMS, or Oracle for short, which is a relational database management system of Oracle corporation), MySQL (MySQL is a small relational database management system of open source code) database or PostgreSQL (PostgreSQL is a free object-relational database server) database, and the target database is a hive (hive is a database warehouse tool based on Hadoop) database. These databases are common and easy-to-operate database management systems and tools, which facilitate the analysis and processing of data in this embodiment.

And S20, marking each community client as a precise identification class or a fuzzy identification class according to the identification information.

After the basic information of all group clients is obtained, because the integrity of the identification information of different group clients is different, the identification information of different group clients is marked as an accurate identification class or a fuzzy identification class according to the identification information of different group clients, and corresponding unique identification is performed on the different group clients, so that the group clients can be identified and integrated no matter whether the identification information of the clients is complete or missing, and the application range of information unique identification is widened, refer to fig. 3, which is a flow chart of step S20 in the information unique identification method provided by the present invention.

As shown in fig. 3, the step S20 includes:

s21, analyzing the identification information of each group client;

s22, judging whether the identification information of each group client contains preset accurate identification information, if so, marking the identification information as an accurate identification class; otherwise, the label is a fuzzy recognition class.

After the basic information of all the group clients is acquired, the identification information of each group client is analyzed to obtain the content contained in the identification information of each group client, whether the preset accurate identification information is contained in the identification information of each group client is sequentially judged, if yes, the identification information is marked as an accurate identification class, and if not, the identification information is marked as a fuzzy identification class, so that the identification classification of the group clients is realized, and a data base is provided for the subsequent targeted identification process. In this embodiment, the preset accurate identification information is preferably a unique and invariable code identifier of an organization code, and the group clients containing the organization code in the identification information are marked as an accurate identification class, so that the group clients containing no organization code can be quickly and accurately identified, and the group clients not containing the organization code are marked as a fuzzy identification class.

And S30, respectively carrying out accurate identification and fuzzy identification on the group clients in the accurate identification class and the fuzzy identification class according to a preset identification rule, and identifying the group clients which are the same client.

In this embodiment, after all group clients are classified, accurate identification and fuzzy identification are performed for different types of group clients, so that the range of all group clients is effectively covered, and the group clients who are the same client in different source databases can be identified, so that the group client data can be managed and analyzed. Please refer to fig. 4, which is a flowchart illustrating step S30 in the method for identifying uniqueness of information according to the present invention.

As shown in fig. 4, the step S30 includes:

s31, detecting the characters of the client names of all group clients, and acquiring the character number and the character content of the client names;

s32, performing unique identification according to preset accurate identification information and a client name of each group client in an accurate identification class, and identifying group clients which are the same client in the accurate identification class;

and S33, performing unique identification according to the identification information of each group client in the fuzzy identification, the word number and the character content of the client name, and identifying the group clients which are the same clients in the fuzzy identification.

In this embodiment, after the group clients are classified, the client names of all the group clients are firstly subjected to character detection to obtain and store the word number and character content of the client name, wherein the character detection and identification can adopt the existing OCR character identification technology, and then according to different client categories, aiming at the clients in the accurate identification class, because the identification information of the clients comprises the preset accurate identification information (organization mechanism code in this embodiment), the unique identification is carried out according to the preset accurate identification information and the client name of each group client in the accurate identification class, and aiming at the clients in the fuzzy identification class, because the identification information does not comprise the preset accurate identification information, the unique identification is carried out according to other contents in the identification information and in combination with the word number of the client name and the character content, thereby ensuring that the clients in the accurate identification class can carry out accurate and rapid identification, and the client in the fuzzy recognition class can be recognized by integrating other basic information, and the client recognition requirements of different information integrity degrees are met.

Referring to fig. 5, a process of accurate identification is shown as a flowchart of step S32 in the information uniqueness identification method provided by the present invention, as shown in fig. 5, the step S32 includes:

s321, randomly selecting one group client in the accurate identification class, and comparing the preset accurate identification information and the client name of the group client with the preset accurate identification information and the client names of other group clients in the accurate identification class;

s322, judging whether group clients with the same preset accurate identification information and the same client name exist according to the comparison result, and if so, identifying the group clients with the same preset accurate identification information and the same client name as the selected group clients as the same clients; if not, identifying the selected group client and other group clients in the accurate identification class as different clients;

and S323, continuously selecting another group client in the precise identification class to perform unique identification with other group clients until all the group clients in the precise identification class are identified.

When accurate identification is carried out, one group client in the accurate identification class is randomly selected, the organization code and the client name of the group client are compared with other group clients in the accurate identification class, unique identification is carried out according to a comparison result, whether the group client with the same organization code and the same client name (the same word number and the same character content) exists or not is judged, if the group client exists, all the group clients with the same organization code and the same client name are identified as the same client with the selected group client, namely, the group client and the selected group client are identified as the same client no matter how many group clients with the same organization code and the same client name are identified, and repeated identification is not needed when the subsequent accurate identification is carried out on all the group clients identified as the same client, so that the identification time is saved; and if not, identifying the selected group client and other group clients in the precise identification class as different clients, and then continuing to select another group client in the precise identification class to perform the identification process until all group clients in the precise identification class are identified.

For example, ten group clients marked as accurate identification classes are obtained from different source databases, and are marked as client 1, client 2, … and client 10, when accurate identification is performed, one of the group clients is arbitrarily selected to start unique identification, for example, client 1 is selected, the organization code and the client name of client 1 are compared with other nine group clients, and the organization code and the client name of client 3 and client 4 are completely the same as client 1, at this time, client 1, client 3 and client 4 are identified as the same client, client data of the three clients can be integrated, and when accurate identification is performed subsequently, client 3 and client 4 do not need to be identified; then, continuously comparing the organization code and the client name of the client 2 with other six group clients to obtain that the organization code and the client name of the client without the group are completely the same as the client 2, and identifying the client 2 and other nine group clients as different clients; and sequentially carrying out unique identification on the client 5, the client 6, … and the client 10 according to the identification process, so that ten clients in the accurate identification class are subjected to unique identification, and the analysis and management of group client data are facilitated.

Please refer to fig. 6, which is a flowchart of step S33 in the information uniqueness identifying method according to the present invention, as shown in fig. 6, the step S33 includes:

s331, judging whether the number of the client name words of each group client in the fuzzy identification class is more than or equal to a preset threshold value;

s332, if the number is larger than or equal to the preset threshold value, performing unique identification according to the word number and the character content of the customer name of the group customer;

s333, if the number is less than the preset threshold value, carrying out unique identification according to the identification information of the group customers, the word number of the customer names and the character content

That is, when fuzzy recognition is performed, different recognition processes are performed according to the number of the client name words of the group clients, and it is first determined whether the number of the client name words of each group client in the fuzzy recognition class is greater than a preset threshold, in this embodiment, the preset threshold is preferably 8, namely, whether the client name of each group client in the fuzzy recognition class is larger than or equal to 8 characters is judged, if the client name is larger than or equal to 8 characters, the probability of different client names is very small due to longer client name, therefore, the unique recognition is carried out according to the number of the client name characters and the character content, if the number of words is less than 8, not only the number of words and the text content of the client name but also the identification information thereof are uniquely identified in order to further confirm the information of the group client, and the words are further classified and identified according to the number of the different client names, and meanwhile, the identification accuracy and the identification efficiency are ensured.

Specifically, please refer to fig. 7, which is a flowchart illustrating step S332 in the information uniqueness identifying method according to the present invention, as shown in fig. 7, the step S332 includes:

s3321, randomly selecting a group client with the client name number more than or equal to a preset threshold in the fuzzy recognition, and comparing the client name with the client names of all the group clients in a character content manner;

s3322, judging whether a group client with the same character content of the client name exists according to the comparison result, and if so, identifying the group client with the same character content and the selected group client as the same client; if not, identifying the selected group client and all other group clients as different clients;

s3323, continuously selecting another group client with the client name word number larger than or equal to the preset threshold value in the fuzzy identification to perform unique identification until all the group clients with the client name word number larger than or equal to the preset threshold value in the fuzzy identification are identified.

When fuzzy recognition is performed, aiming at the situation that the number of name words of a client is more than or equal to a preset threshold (8 words in the embodiment), firstly, a group client with the number of name words more than or equal to 8 words in fuzzy recognition is arbitrarily selected, the name of the group client is compared with the names of all group clients (including group clients in precise recognition and fuzzy recognition), the character content is compared, uniqueness recognition is performed according to the comparison result, whether a group client with the same name of the client or not exists is judged, if yes, the group client with the same character content is recognized as the same client as the selected group client, the group client and the selected group client are recognized as the same client no matter how many group clients with the same name of the client are recognized, and repeated recognition is not needed in the subsequent fuzzy recognition, the time consumption for identification is saved; if not, the selected group client and all other group clients are identified as different clients, and then another group client with the client name larger than or equal to 8 characters in the fuzzy identification class is continuously selected to carry out the identification process until all the group clients with the client names larger than or equal to 8 characters in the fuzzy identification class are identified.

For example, ten group clients marked as fuzzy recognition class and having client name number greater than or equal to 8 characters from among the group clients acquired from different source databases are marked as client 11, client 12, …, and client 20, and when fuzzy recognition is performed, one of the group clients is arbitrarily selected to start unique recognition, for example, client 11 is selected to compare its client name with all other group clients, since it may happen that client 11 is the same client as the group client in the precise recognition class, but because organization code is missing in its identification information, it is marked as fuzzy recognition class, therefore, when fuzzy recognition is performed, it is necessary to compare the names of the selected group client with all other group clients to ensure the comprehensiveness and accuracy of recognition, and then assume that client 2, client 2 in the precise recognition class, and client 20 are obtained by comparison, The client name literal contents of the client 13 and the client 14 in the fuzzy recognition class are completely the same as the client 11, so that the client 2, the client 11, the client 13 and the client 14 are recognized as the same client, and the client data of the client 2, the client 11, the client 13 and the client 14 can be integrated; then, the client name of the client 12 is continuously compared with other six group clients, and the client name of no group client is completely the same as the client 12, and at the moment, the client 12 and all other group clients are identified as different clients; then, the customer 15, the customer 16, the customer … and the customer 20 are uniquely identified according to the identification process, and the unique identification process of the group customer with the name word number larger than 8 words is completed.

Further, please refer to fig. 8, which is a flowchart of step S333 in the information uniqueness identifying method provided by the present invention, as shown in fig. 8, step S333 includes:

s3331, randomly selecting a group client with the client name number smaller than a preset threshold in the fuzzy recognition, and comparing the client name with the client names of all the group clients in a text content manner;

s3331, judging whether a group client with the same client name and the same text content exists according to the comparison result, if so, continuously judging whether the group client with the same text content and the selected group client have any same identification information, and identifying the group client with the same text content and any same identification information and the selected group client as the same client; if not, identifying the selected group client and all other group clients as different clients;

s3331, continuously selecting another group client with the client name word number smaller than the preset threshold value in the fuzzy identification to perform unique identification until all the group clients with the client name word number smaller than the preset threshold value in the fuzzy identification are identified.

When fuzzy recognition is performed, aiming at the situation that the number of name words of a client is less than a preset threshold (8 words in the embodiment), a group client with the number of name words less than 8 words in the fuzzy recognition class is selected at will, the client name of the group client is compared with the client names of all the group clients (including the group clients in the precise recognition class and the fuzzy recognition class), unique recognition is performed according to the comparison result, whether the group client with the same client name and the same character content exists is judged, if so, because the selected group client name is shorter and the duplication situation is easy to occur, whether the group client with the same character content and the selected group client have any same identification information is continuously judged, for example, at least one of a worker registration number, a tax registration number and a business license number is the same, and the character content of the client name is the same, and the group client with any identical identification information and the selected group client are identified as the same client; if not, identifying the selected group client and all other group clients as different clients, then continuing to select another group client with the client name smaller than 8 characters in the fuzzy identification class to perform the identification process until all the group clients with the client name smaller than 8 characters in the fuzzy identification class are identified, and finishing the information uniqueness identification with the client name smaller than 8 characters in the fuzzy identification class by combining the identification information and the client name.

And S40, acquiring the identification results of the accurate identification and the fuzzy identification, and integrating the basic information of all group customers who are the same customers to obtain the uniquely identified group customer information according to the identification results.

In this embodiment, after performing accurate identification and fuzzy identification on different types of group clients, all group clients that are the same client as each other are identified, at this time, identification results of the accurate identification and the fuzzy identification are obtained, basic information of the group clients that are the same client as each other is integrated according to the identification results, specifically, all client names that are the same client as each other are unified, and respective identification information is complementarily integrated to obtain uniquely identified group client information, client data stored in different source databases of a certain group client can be obtained at one time according to the uniquely identified group client information, so that unified integration analysis of the same client data in different source databases is realized, data analysis can be performed according to the identified and integrated client data, and the data life cycle of the group client can be comprehensively analyzed by combining the user data stored in different industry companies, Preferred consumer willingness, risk control information, etc., which facilitates group client follow-up and management.

As shown in fig. 9, based on the above information uniqueness identification method, the present invention further provides an information uniqueness identification application server, which includes a processor 10, a memory 20, and a display 30. Fig. 9 shows only some of the components of the application server uniquely identified by the information, but it is to be understood that not all of the shown components are required to be implemented, and that more or fewer components may be implemented instead.

The memory 20 may in some embodiments be an internal storage unit of the application server uniquely identified by the information, such as a hard disk or a memory of the application server. The memory 20 may also be an external storage device of the application server identified uniquely by the information in other embodiments, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like equipped on the application server identified uniquely by the information. Further, the memory 20 may also include both an internal storage unit of the uniquely identified application server and an external storage device. The memory 20 is used for storing application software installed in the application server uniquely identified by the information and various types of data, such as program codes of the application server uniquely identified by the installation information. The memory 20 may also be used to temporarily store data that has been output or is to be output. In some embodiments, the memory 20 stores an information uniqueness identifying program 40, and the information uniqueness identifying program 40 can be executed by the processor 10, so as to implement the information uniqueness identifying method of the embodiments of the present application.

The processor 10 may be a Central Processing Unit (CPU), a microprocessor or other data Processing chip in some embodiments, and is used for running program codes stored in the memory 20 or Processing data, such as executing the authority authentication method.

The display 30 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch panel, or the like in some embodiments. The display 30 is used for displaying information of the application server uniquely identified by the information and for displaying a visualized user interface, such as an identification result interface. The components 10-30 of the application server uniquely identified by the information communicate with each other via a system bus.

In some embodiments, the following steps are implemented when processor 10 executes unique identification of information program 40 in memory 20:

and acquiring identification results of accurate identification and fuzzy identification, and integrating basic information of all group customers who are the same customer to obtain the group customer information of unique identification according to the identification results.

Further, in the application server uniquely identified by the information, the step of marking each group client as a precise identification class or a fuzzy identification class according to the identification information includes:

analyzing the identification information of each group client;

According to the preset identification rule, group clients in the accurate identification class and the fuzzy identification class are respectively subjected to accurate identification and fuzzy identification, and the step of identifying the group clients which are the same client comprises the following steps:

According to the preset accurate identification information and the client name of each group client in the accurate identification class, carrying out uniqueness identification, wherein the step of identifying the group clients which are the same client in each other in the accurate identification class comprises the following steps:

The unique identification is carried out according to the identification information of each group client in the fuzzy identification class, the word number and the character content of the client name, and the step of identifying the group clients which are the same clients in the fuzzy identification class comprises the following steps:

If the number of words is larger than or equal to the preset threshold, the step of carrying out unique identification according to the word number and the character content of the customer name of the group customer comprises the following steps:

If the number of the group clients is smaller than the preset threshold value, the step of performing unique identification according to the identification information of the group clients, the word number of the client name and the character content comprises the following steps:

Please refer to fig. 10, which is a functional block diagram of an application server for installing a unique identifier according to a preferred embodiment of the present invention. In this embodiment, the application server installed with the information unique identifier may be divided into one or more modules, and the one or more modules are stored in the memory 20 and executed by one or more processors (in this embodiment, the processor 10) to complete the present invention. For example, in fig. 10, the application server in which the information uniqueness identifying program is installed may be divided into an acquisition module 21, a classification module 22, an identification module 23, and an integration module 24. The module referred to in the present invention means a series of instruction segments of a computer program capable of performing a specific function, which is more suitable than a program for describing the execution process of the community client unique identification program in the application server uniquely identified by the community client. The following description will specifically describe the functionality of the modules 21-24.

An obtaining module 21, configured to obtain basic information of the group client stored in each source database, where the basic information includes a client name and identification information;

the classification module 22 is configured to mark each group client as an accurate identification class or a fuzzy identification class according to the identification information;

the identification module 23 is configured to perform accurate identification and fuzzy identification on the group clients in the accurate identification class and the fuzzy identification class according to a preset identification rule, and identify the group clients that are the same client;

and the integration module 24 is configured to obtain the identification results of the precise identification and the fuzzy identification, and integrate the basic information of all group customers who are the same customer as each other according to the identification results to obtain the group customer information of the unique identification.

The classification module 22 includes:

the analysis unit is used for analyzing the identification information of each group client;

the classification unit is used for judging whether the identification information of each group client contains preset accurate identification information or not, and if so, marking the identification information as an accurate identification class; otherwise, the label is a fuzzy recognition class.

The identification module 23 includes:

the detection unit is used for carrying out character detection on the client names of all group clients and acquiring the word number and the character content of the client names;

the system comprises an accurate identification unit, a group identification unit and a group identification unit, wherein the accurate identification unit is used for carrying out unique identification according to preset accurate identification information and a client name of each group client in an accurate identification class and identifying the group clients which are the same client in the accurate identification class;

and the fuzzy identification unit is used for carrying out unique identification according to the identification information of each group client in the fuzzy identification, the word number and the character content of the client name and identifying the group clients which are the same clients in the fuzzy identification.

The accurate recognition unit includes:

the first comparison subunit is used for randomly selecting one group client in the accurate identification class and comparing the preset accurate identification information and the client name of the group client with the preset accurate identification information and the client names of other group clients in the accurate identification class;

the first identification subunit is used for judging whether group clients with the same preset accurate identification information and the same client name exist according to the comparison result, and if so, identifying the group clients with the same preset accurate identification information and the same client name as the selected group clients as the same clients; and if not, identifying the selected group client and other group clients in the precise identification class as different clients.

The blur identification unit includes:

the first judgment subunit is used for judging whether the number of the client name words of each group client in the fuzzy identification class is greater than or equal to a preset threshold value or not;

the second identification subunit is used for performing unique identification according to the word number and the character content of the client name of the group client if the number is larger than or equal to a preset threshold;

and the third identification subunit is used for performing unique identification according to the identification information of the group customers, the word number of the customer names and the character content if the number is smaller than the preset threshold value.

The second identification subunit comprises;

the second comparison subunit is used for randomly selecting a group client with the client name number greater than or equal to a preset threshold in the fuzzy identification class and comparing the client name with the client names of all the group clients in a text content manner;

a second judging subunit, configured to judge whether there is a group client with the same text content as the client name according to the comparison result, and if so, identify the group client with the same text content as the selected group client; if not, the selected group client is identified as a different client from all other group clients.

The third identifier unit comprises:

the third comparison subunit is used for randomly selecting a group client with the client name number smaller than a preset threshold in the fuzzy recognition class and comparing the client name with the client names of all the group clients in a text content manner;

a third judging subunit, configured to judge whether there is a group client with the same name and the same text content, and if yes, continue to judge whether the group client with the same text content and the selected group client have any identification information, and identify the group client with the same text content and any identification information as the same client; if not, the selected group client is identified as a different client from all other group clients.

Based on the above information uniqueness identification method and application server, the present invention also provides an information uniqueness identification system, referring to fig. 11, which includes a plurality of source databases 110 and the application server 120 for information uniqueness identification as described above.

Each source database 110 is configured to store basic information of a group client, and the application server 120 is configured to obtain the basic information of the group client stored in each source database, where the basic information includes a client name and identification information; marking each group client as an accurate identification class or a fuzzy identification class according to the identification information; respectively carrying out accurate identification and fuzzy identification on the group clients in the accurate identification class and the fuzzy identification class according to a preset identification rule, and identifying the group clients which are the same client; and acquiring identification results of accurate identification and fuzzy identification, and integrating basic information of all group customers who are the same customer to obtain the group customer information of unique identification according to the identification results.

The work flow of the information uniqueness identification system in the embodiment is as follows:

the application server acquires basic information of the group client stored in each source database, wherein the basic information comprises a client name and identification information;

the application server marks each group client as an accurate identification class or a fuzzy identification class according to the identification information;

the application server respectively carries out accurate identification and fuzzy identification on the group clients in the accurate identification class and the fuzzy identification class according to a preset identification rule, and identifies the group clients which are the same client;

the application server acquires the identification results of the accurate identification and the fuzzy identification, and integrates the basic information of all group clients who are the same client with each other according to the identification results to obtain the group client information of the unique identification.

Further, in the information uniqueness identification system, the process of the application server marking each group client as a precise identification class or a fuzzy identification class according to the identification information includes:

the application server analyzes the identification information of each group client;

the application server judges whether the identification information of each group client contains preset accurate identification information or not, and if so, the identification information is marked as an accurate identification class; otherwise, the label is a fuzzy recognition class.

The application server respectively carries out accurate identification and fuzzy identification on the group clients in the accurate identification class and the fuzzy identification class according to a preset identification rule, and the flow of identifying the group clients which are the same client each other comprises the following steps:

the application server performs character detection on the client names of all group clients to acquire the word number and the character content of the client names;

the application server performs unique identification according to preset accurate identification information and a client name of each group client in an accurate identification class, and identifies the group clients which are the same client in the accurate identification class;

and the application server performs unique identification according to the identification information of each group client in the fuzzy identification class, the word number and the character content of the client name, and identifies the group clients which are the same client in the fuzzy identification class.

The application server carries out uniqueness recognition according to preset accurate recognition information and a client name of each group client in an accurate recognition class, and the process of recognizing the group clients which are the same client in the accurate recognition class comprises the following steps:

the application server randomly selects one group client in the accurate identification class, and compares the preset accurate identification information and the client name of the group client with the preset accurate identification information and the client names of other group clients in the accurate identification class;

the application server judges whether group clients with the same preset accurate identification information and the same client name exist according to the comparison result, and if the group clients with the same preset accurate identification information and the same client name exist, the group clients with the same preset accurate identification information and the same client name are identified as the same client as the selected group client; if not, identifying the selected group client and other group clients in the accurate identification class as different clients;

the application server continues to select another group client in the precise identification class to perform unique identification with other group clients until all the group clients in the precise identification class are identified.

The application server carries out unique identification according to the identification information of each group client in the fuzzy identification, the word number and the character content of the client name, and the flow for identifying the group clients which are the same clients in the fuzzy identification comprises the following steps:

the application server judges whether the number of the client name words of each group client in the fuzzy identification class is greater than or equal to a preset threshold value or not;

if the number of the words is larger than or equal to the preset threshold value, the application server carries out unique identification according to the word number and the character content of the client name of the group client;

if the number of the group clients is smaller than the preset threshold value, the application server carries out unique identification according to the identification information of the group clients, the word number of the client names and the character content.

If the number of words is larger than or equal to the preset threshold, the process that the application server carries out unique identification according to the word number and the word content of the client name of the group client comprises the following steps:

the application server randomly selects a group client with the client name word number larger than or equal to a preset threshold in the fuzzy recognition class, and compares the client name with the client names of all the group clients in a text content manner;

the application server judges whether a group client with the identical text content of the client name exists or not according to the comparison result, and if the group client with the identical text content exists, the group client and the selected group client are identified as the same client; if not, identifying the selected group client and all other group clients as different clients;

and the application server continues to select another group client with the client name word number larger than or equal to the preset threshold value in the fuzzy identification class for unique identification until all the group clients with the client name word number larger than or equal to the preset threshold value in the fuzzy identification class are identified.

If the number of the group clients is smaller than the preset threshold, the process that the application server carries out unique identification according to the identification information of the group clients, the word number of the client names and the word content comprises the following steps:

the application server randomly selects a group client with the client name word number smaller than a preset threshold value in the fuzzy recognition class, and compares the client name with the client names of all the group clients in a text content manner;

the application server judges whether a group client with the identical character content of the client name exists according to the comparison result, if so, the application server continuously judges whether the group client with the identical character content and the selected group client have any identical identification information, and identifies the group client with the identical character content and any identical identification information and the selected group client as the same client; if not, identifying the selected group client and all other group clients as different clients;

and the application server continues to select another group client with the client name word number smaller than the preset threshold value in the fuzzy identification class for unique identification until all the group clients with the client name word number smaller than the preset threshold value in the fuzzy identification class are identified.

In summary, in the information uniqueness identification method, the application server, the system and the storage medium provided by the present invention, the information uniqueness identification method obtains the basic information of the group client stored in each source database, where the basic information includes the client name and the identification information; then marking each group client as an accurate identification class or a fuzzy identification class according to the identification information; then, according to a preset identification rule, group clients in the accurate identification class and the fuzzy identification class are respectively subjected to accurate identification and fuzzy identification, and the group clients which are the same client are identified; and then acquiring identification results of accurate identification and fuzzy identification, and integrating basic information of all group customers who are the same customer to obtain the group customer information of unique identification according to the identification results. Accurate identification or fuzzy identification can be respectively carried out according to the types of different group customers, and the problem that part of group customers cannot carry out uniqueness identification and data integration due to incomplete customer information is solved.

Of course, it will be understood by those skilled in the art that all or part of the processes of the methods of the above embodiments may be implemented by a computer program instructing relevant hardware (such as a processor, a controller, etc.), and the program may be stored in a computer readable storage medium, and when executed, the program may include the processes of the above method embodiments. The storage medium may be a memory, a magnetic disk, an optical disk, etc.

It is to be understood that the invention is not limited to the examples described above, but that modifications and variations may be effected thereto by those of ordinary skill in the art in light of the foregoing description, and that all such modifications and variations are intended to be within the scope of the invention as defined by the appended claims.

Claims

1. An information uniqueness identification method is characterized by comprising the following steps:

acquiring identification results of accurate identification and fuzzy identification, and integrating basic information of all group customers who are the same customer to obtain uniquely identified group customer information according to the identification results;

according to the identification information of each group client in the fuzzy identification class, the word number and the character content of the client name, carrying out unique identification, and identifying the group clients which are the same client in the fuzzy identification class;

2. The information uniqueness identifying method according to claim 1, wherein the step of marking each community client as a precise identification class or a fuzzy identification class according to the identification information comprises:

analyzing the identification information of each group client;

3. The information uniqueness recognition method according to claim 2, wherein the group clients in the precise recognition class and the fuzzy recognition class are precisely recognized and fuzzy recognized respectively according to a preset recognition rule, and the step of recognizing the group clients that are the same client includes:

and performing unique identification according to preset accurate identification information and a client name of each group client in the accurate identification class, and identifying the group clients which are the same client in the accurate identification class.

4. The information uniqueness recognition method according to claim 3, wherein the uniqueness recognition is performed according to preset accurate recognition information and a client name of each group client in an accurate recognition class, and the step of recognizing the group clients that are the same client in the accurate recognition class comprises:

5. The information uniqueness recognition method according to claim 1, wherein the step of performing uniqueness recognition according to the word count and the character content of the client name of the group client if the number is equal to or greater than a preset threshold value includes:

6. The information uniqueness recognition method according to claim 1, wherein if the value is smaller than a preset threshold, the step of performing uniqueness recognition according to the identification information of the group customer, the word number of the customer name and the text content comprises:

7. An application server uniquely identified by information, comprising: a processor, a memory, and a communication bus; the memory has stored thereon a computer readable program executable by the processor;

the processor, when executing the computer readable program, implements the steps in the information uniqueness identifying method as recited in any one of claims 1 to 6.

8. A computer-readable storage medium storing one or more programs, the one or more programs being executable by one or more processors to perform the steps of the method for uniquely identifying information according to any one of claims 1 to 6.

9. An information uniqueness identification system comprising a plurality of source databases, further comprising an application server for information uniqueness identification according to claim 7;