CN111859055A - Intelligent data retrieval matching system based on big data - Google Patents

Intelligent data retrieval matching system based on big data Download PDF

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CN111859055A
CN111859055A CN202010624978.0A CN202010624978A CN111859055A CN 111859055 A CN111859055 A CN 111859055A CN 202010624978 A CN202010624978 A CN 202010624978A CN 111859055 A CN111859055 A CN 111859055A
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technical
information
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王刚
曹兰平
李庆刚
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Jiangsu Zhiling Technology Consulting Co Ltd
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Jiangsu Zhiling Technology Consulting Co Ltd
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/906—Clustering; Classification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/901—Indexing; Data structures therefor; Storage structures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
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    • G06F16/90335—Query processing

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Abstract

The invention discloses a data intelligent retrieval matching system based on big data, which comprises: the system comprises a client information management module, a technical management module, a storage module and an activity information management module, and simultaneously provides a data intelligent retrieval matching method based on big data, which comprises the following steps: after entering the system, the client registers basic information and classifies the client according to the registered information; managing technical information, and providing inquiry and screening technologies according to key words input by a client; storing the client information and the technical information, and updating the stored content according to the modification of the information; the technical latest information is disclosed and a feedback way is provided for the client to evaluate. According to the invention, intelligent data retrieval matching based on big data is realized, technologies are screened according to user requirements, corresponding technologies which best meet the user requirements are recommended for the user, the user screening efficiency is improved, and a good reference basis is provided for the selection of the user.

Description

Intelligent data retrieval matching system based on big data
Technical Field
The invention relates to the field of intelligent data retrieval, in particular to a system and a method for intelligently retrieving and matching data based on big data.
Background
With the development of information technology, big data becomes an indispensable technology in the information age, the big data is a data set with a large scale which greatly exceeds the capability range of traditional database software tools in the aspects of acquisition, storage, management and analysis, and has the four characteristics of massive data scale, rapid data circulation, various data types and low value density, the strategic significance of the big data technology is not to master huge data information, but to perform specialized processing on the meaningful data, in the prior art, the big data is applied to data intelligent retrieval, technical personnel gradually tend to perform data processing through the big data technology, but the existing data processing system has the following problems:
1. the traditional data retrieval system is not intelligent enough, the databases are independent, and information sharing among a plurality of databases cannot be realized;
2. the description information of the technical achievement field usually has errors, and the description in the system is slightly different from the actual technology;
3. in the prior art, only corresponding technical service templates are provided for users, and system upgrading and updating cannot be performed through the use of the system by the users.
Disclosure of Invention
The invention aims to provide a data intelligent retrieval matching system and method based on big data, and aims to solve the problems in the prior art.
In order to achieve the purpose, the invention provides the following technical scheme:
a big data based intelligent data retrieval matching system comprises: the system comprises a client information management module, a technical management module, a storage module and an activity information management module;
the client information management module carries out basic information statistics on clients entering the system and classifies the basic information of the clients;
the technical management module is used for managing technical information of the client and providing query technology and screening technology management for the user;
the storage module is used for storing the client basic information in the client information management module and the technical information in the technical management module;
and the activity information management module is used for publishing the technical information generated by the customer information management module and the technical management module to the customer and evaluating the credit of the system.
Preferably, the customer information management module comprises a customer login unit, a customer category classification unit and a customer information entry unit;
the client login unit is used for carrying out technical management on a system user when the system user enters the system and confirming the identity information of the system user;
The client category classification unit is used for classifying clients into common clients, technical staff with technical achievements and technical demand staff, and corresponding to different categories of users to provide corresponding technical services for the users;
the client information input unit is used for registering basic information of all client information according to different categories, uploading a registration result to the storage module, and providing a communication mode and a technical communication path for a user when clients of different categories need technical communication.
Preferably, the technical management module comprises a technical demand management unit, a technical result management unit, a technical inquiry unit and a technical tracking unit;
the technical requirement management unit is used for searching the technical requirements of the client after the client logs in and matching the technical requirements of the client with the corresponding technical achievements according to the technical requirements of the client;
searching the technical requirements of a client, inputting legal requirement keywords to be searched by the client, and inputting the requirement keywords to a technical query unit;
if the requirement key words are legal, similarity calculation is carried out on the requirement key words and the key words stored in the storage module, and K is { K ═ K { (K)1，k2，k3，...，knIs a set of keywords, according to the formula:
Figure BDA0002564451000000031
Wherein,
Figure BDA0002564451000000032
as a keyword kn1，kn2The degree of similarity to the set of keywords,
Figure BDA0002564451000000033
has a value range of [ -1, 1 [)]，
Figure BDA0002564451000000034
The larger the value of (A), the greater the similarity between the keyword and the keyword set, sim (k)n1kn，kn2kn) Represented in a set of keywords K, the keywords Kn1And a keyword kn2The similarity of (2);
when in use
Figure BDA0002564451000000035
Then, the requirement key word input by the client is shown as a legal requirement key word;
the user requirements are matched through legal judgment of the keywords, the searching and screening efficiency of the user is improved, and the cost is saved;
the technical result management unit is used for carrying out label classification on the technical results and classifying the technical results as labels according to the fields and key technologies of the technical results;
scoring the newly input technical result in each technical field respectively, selecting the technical field with the highest score as a technical field label of the technical result, simultaneously calculating the distribution frequency of key technologies in the technical result, and determining the key technology with the highest distribution frequency as a key technical label;
the technical classification field and the search keywords are determined by determining the technical field labels and the technical distribution frequency, so that the client can conveniently and directly match the technology the same as the search keywords during searching, and the searching and screening efficiency is improved.
Wherein, the technical field set accessed by the technical result is W ═ { W ═ W 1，W2，W3，…WnAnd scoring the technical achievements in the technical field according to a formula:
Figure BDA0002564451000000041
wherein S isiFor technical field scoring, | Smax-WiI is the absolute value of the difference between the current highest score of the technical achievement and the current technical field;
calculating the key technology with the highest distribution frequency according to a formula:
Figure BDA0002564451000000042
wherein E is the distribution frequency of technical achievements in the key technology, JnFor all key technologies, JdFor the key distribution frequency of the current technology, Jn-dKey distribution frequencies of the remaining technologies;
calculating the key distribution frequency of the prior art, wherein the higher the distribution frequency is, the higher the key degree of the technology is, and the higher the possibility of being used as a key technology is;
the technology query unit is used for a client to query and screen the required technology and select the technology meeting the intention according to the description of the recommended technology;
the technology tracking unit is used for tracking the technical requirements of the clients and the subsequent technical development, recording the subsequent implementation process of the technology and updating the technical state.
Preferably, the storage module comprises a customer information storage unit and a technical information storage unit;
the client information storage unit is used for storing client information and comprises: the client name, the client contact information, the enterprise where the client is located, the client requirement and the client category;
The technical information storage unit is used for storing all technical information, including: technical name, technical field, technical inventor, technical company, key technical composition, technical point and current technical state;
wherein, the storage unit performs data update on the client information and the technical information at fixed time intervals as the technical state changes.
Preferably, the activity information management module comprises an information publishing unit and a client feedback unit;
the information publishing unit is used for disclosing the latest information of the technology to the client, wherein the latest information comprises technical inventor information and technical specific information;
the customer feedback unit provides an evaluation service for the customer, the customer evaluates the credit of the system according to the information obtained by the technical service provided by the technical management module, the credit evaluation uses (a, b) to represent the credit score of the customer on the corresponding unit of the technical management module, and the credit evaluation is carried out according to a formula:
an＝∑u×an-1+s；
bn＝∑u×bn-1+1-s；
wherein u is the functional unit score under the technology management module, s represents the feedback evaluation to the technology management unit n, and s is a good score of 1;
and evaluating the system by the client to know whether the service provided by the client to the system is satisfied, and timely and correspondingly modifying and upgrading the system according to the credit score.
A data intelligent retrieval matching method based on big data comprises the following steps:
step S1, after the client enters the system, the basic information registration is carried out, and the client is classified according to the registration information;
step S2, managing the technical information, providing inquiry and screening technique according to the key words input by the client;
step S3, storing the client information and the technical information, and updating the stored content according to the modification of the information;
and step S4, disclosing the latest technical information and providing a feedback path for the client to evaluate.
Preferably, the step S1 includes:
step S11, when the system user enters the system, the technical management is carried out to the system user to confirm the identity information of the system user;
step S12, dividing the customers into common customers, technical staff with technical achievements and technical demand staff, corresponding to different types of users, and providing corresponding technical services for the users;
and step S13, registering the basic information of the client information according to different categories, uploading the registration result to a storage module, and providing a communication mode and a technical communication path for the user when the clients of different categories need to perform technical communication.
Preferably, the step S2 includes:
Step S21, searching the technical requirements of the customer, and matching the technical requirements of the customer with the corresponding technical achievements according to the technical requirements of the customer, including:
a client inputs legal requirement keywords to be searched, and inputs the requirement keywords into a technical query unit;
if the requirement key words are legal, similarity calculation is carried out on the requirement key words and the key words stored in the storage module, and K is { K ═ K { (K)1，k2，k3，...，knIs a set of keywords, according to the formula:
Figure BDA0002564451000000071
wherein,
Figure BDA0002564451000000072
as a keyword kn1，kn2The degree of similarity to the set of keywords,
Figure BDA0002564451000000073
has a value range of [ -1, 1 [)]，
Figure BDA0002564451000000074
The larger the value of (A), the greater the similarity between the keyword and the keyword set, sim (k)n1kn，kn2kn) Represented in a set of keywords K, the keywords Kn1And a keyword kn2The similarity of (2);
when in use
Figure BDA0002564451000000075
If so, indicating that the requirement keyword input by the customer is a legal requirement keyword, and entering step S23;
step S22, performing label classification on the technical result, and classifying the technical result as a label according to the field and the key technology of the technical result, wherein the label classification comprises the following steps:
scoring the newly input technical result in each technical field respectively, selecting the technical field with the highest score as a technical field label of the technical result, simultaneously calculating the distribution frequency of key technologies in the technical result, and determining the key technology with the highest distribution frequency as a key technical label;
Wherein, the technical field set accessed by the technical result is W ═ { W ═ W1，W2，W3，…WnAnd scoring the technical achievements in the technical field according to a formula:
Figure BDA0002564451000000081
wherein S isiFor technical field scoring, | Smax-WiI is the absolute value of the difference between the current highest score of the technical achievement and the current technical field;
calculating the key technology with the highest distribution frequency according to a formula:
Figure BDA0002564451000000082
wherein E is the distribution frequency of technical achievements in the key technology, JnFor all key technologies, JdFor the key distribution frequency of the current technology, Jn-dKey distribution frequencies of the remaining technologies;
calculating the key distribution frequency of the prior art, wherein the higher the distribution frequency is, the higher the technical key degree is, and the higher the possibility of being used as a key technology is;
step S23, according to the legal requirement key words of the client in the step S21, the technology required by the client is inquired and screened, and according to the description of the recommended technology, the technology meeting the intention is selected;
step S24, tracking the technical requirements of the customer and the subsequent technical development, recording the subsequent implementation progress of the technology, and updating the technical state.
Preferably, the step S3 includes:
step S31, storing the customer information;
step S32, all technical information is stored.
Preferably, the step S4 includes:
Step S41, the latest information of the technology is disclosed to the client;
step S42, the customer evaluates the credit of the system according to the information obtained by the technical service provided by the technical management module, the credit evaluation uses (a, b) to represent the credit rating of the customer to the corresponding unit of the technical management module, according to the formula:
an＝∑u×an-1+s；
bn＝∑u×bn-1+1-s；
wherein u is the functional unit score under the technology management module, s represents the feedback evaluation to the technology management unit n, and s is a good score of 1.
Compared with the prior art, the invention has the beneficial effects that:
1. the module units are connected to realize data sharing, data information interaction is realized through data storage, and intelligent processing of the data information is realized;
2. the system grading method has the advantages that problems existing in the system can be known in time according to grading of the system by a client, the actual technology is adjusted according to specific problems, the screening time is saved when the client screens the technology, and the client requirements can be met quickly under the condition that the client and the system achieve consensus;
3. through similarity calculation of the keywords and the keyword set, accuracy of data retrieval and screening and retrieval efficiency are improved.
Drawings
In order that the present invention may be more readily and clearly understood, a more particular description of the invention briefly described above will be rendered by reference to specific embodiments that are illustrated in the appended drawings.
FIG. 1 is a schematic diagram of a module structure of an intelligent data retrieval and matching system based on big data according to the present invention;
FIG. 2 is a flow chart of a data intelligent retrieval matching method based on big data according to the present invention;
FIG. 3 is a flow chart of the functional implementation of the intelligent data retrieval and matching method based on big data according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1 to 3, in an embodiment of the present invention, an intelligent data retrieval and matching system based on big data includes: customer information management module, technical management module, storage module and activity information management module, include:
step S1, after the client enters the system, the basic information registration is carried out, and the client is classified according to the registration information;
step S2, managing the technical information, providing inquiry and screening technique according to the key words input by the client;
Step S3, storing the client information and the technical information, and updating the stored content according to the modification of the information;
and step S4, disclosing the latest technical information and providing a feedback path for the client to evaluate.
The customer information management module comprises a customer login unit, a customer category classification unit and a customer information input unit, and comprises:
step S11, when the system user enters the system, the technical management is carried out to the system user to confirm the identity information of the system user;
step S12, dividing the customers into common customers, technical staff with technical achievements and technical demand staff, corresponding to different types of users, and providing corresponding technical services for the users;
and step S13, registering the basic information of the client information according to different categories, uploading the registration result to a storage module, and providing a communication mode and a technical communication path for the user when the clients of different categories need to perform technical communication.
The technical management module comprises a technical demand management unit, a technical result management unit, a technical inquiry unit and a technical tracking unit, and comprises:
step S21, searching the technical requirements of the customer, and matching the technical requirements of the customer with the corresponding technical achievements according to the technical requirements of the customer, including:
A client inputs legal requirement keywords to be searched, and inputs the requirement keywords into a technical query unit;
if the requirement key words are legal, similarity calculation is carried out on the requirement key words and the key words stored in the storage module, and K is { K ═ K { (K)1，k2，k3，...，k6Is a set of keywords, according to the formula:
Figure BDA0002564451000000111
wherein,
Figure BDA0002564451000000112
as a keyword kn1，kn2The similarity with the keyword set K is determined,
Figure BDA0002564451000000113
has a value range of [ -1, 1 [)]，
Figure BDA0002564451000000114
Representing that the similarity between the keywords and the keyword set is 0.82;
when in use
Figure BDA0002564451000000115
If so, indicating that the requirement keyword input by the customer is a legal requirement keyword, and then performing step S23;
step S22, performing label classification on the technical result, and classifying the technical result as a label according to the field and the key technology of the technical result, wherein the label classification comprises the following steps:
scoring the newly input technical result in each technical field respectively, selecting the technical field with the highest score as a technical field label of the technical result, simultaneously calculating the distribution frequency of key technologies in the technical result, and determining the key technology with the highest distribution frequency as a key technical label;
wherein, the technical field set accessed by the technical result is W ═ { W ═ W1，W2，W3，…WnAnd scoring the technical achievements in the technical field according to a formula:
Figure BDA0002564451000000121
wherein S is iFor technical field scoring, | Smax-WiI is the absolute value of the difference between the current highest score of the technical achievement and the current technical field;
calculating the key technology with the highest distribution frequency according to a formula:
Figure BDA0002564451000000122
wherein E is the distribution frequency of technical achievements in the key technology, JnFor all key technologies, JdFor the key distribution frequency of the current technology, Jn-dKey distribution frequencies of the remaining technologies;
calculating the key distribution frequency of all the technologies, wherein the lower the distribution frequency is, the higher the key degree is, and the higher the possibility of being used as a key technology is;
step S23, according to the legal requirement key words of the client in the step S21, the technology required by the client is inquired and screened, and according to the description of the recommended technology, the technology meeting the intention is selected;
step S24, tracking the technical requirements of the customer and the subsequent technical development, recording the subsequent implementation progress of the technology, and updating the technical state.
The storage module comprises a client information storage unit and a technical information storage unit, and comprises:
step S31, storing customer information, wherein the customer information comprises customer name, customer contact information, enterprise where the customer is located, customer requirements and customer category;
step S32, storing all technical information, wherein the technical information comprises technical names, technical fields, technical inventers, technical companies, key technical compositions, technical points and current technical states;
Wherein, the storage unit performs data update on the client information and the technical information at fixed time intervals as the technical state changes.
The activity information management module comprises an information publishing unit and a client feedback unit, and comprises:
step S41, the latest information of the technology is disclosed to the client;
step S42, the customer evaluates the credit of the system according to the information obtained by the technical service provided by the technical management module, the credit evaluation uses (a, b) to represent the credit rating of the customer to the corresponding unit of the technical management module, according to the formula:
an＝∑u×an-1+s＝4.5×4+0＝18；
bn＝∑u×bn-1+1-s＝4.5×3.2+1-0＝15.4；
wherein u is the functional unit score under the technology management module, s represents the feedback evaluation to the technology management unit n, and s is a good score of 1.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.

Claims (10)

1. A big data based intelligent data retrieval matching system is characterized by comprising: the system comprises a client information management module, a technical management module, a storage module and an activity information management module;
the client information management module carries out basic information statistics on clients entering the system and classifies the basic information of the clients;
the technical management module is used for managing technical information of the client and providing query technology and screening technology management for the user;
the storage module is used for storing the client basic information in the client information management module and the technical information in the technical management module;
and the activity information management module is used for publishing the technical information generated by the customer information management module and the technical management module to the customer and evaluating the credit of the system.
2. The big data-based intelligent data retrieval and matching system according to claim 1, wherein the customer information management module comprises a customer login unit, a customer category classification unit and a customer information entry unit;
the client login unit is used for carrying out technical management on a system user when the system user enters the system and confirming the identity information of the system user;
The client category classification unit is used for classifying clients into common clients, technical staff with technical achievements and technical demand staff, and corresponding to different categories of users to provide corresponding technical services for the users;
the client information input unit is used for registering basic information of all client information according to different categories, uploading a registration result to the storage module, and providing a communication mode and a technical communication path for a user when clients of different categories need technical communication.
3. The big data-based intelligent data retrieval and matching system according to claim 1, wherein the technical management module comprises a technical demand management unit, a technical result management unit, a technical inquiry unit and a technical tracking unit;
the technical requirement management unit is used for searching the technical requirements of the client after the client logs in and matching the technical requirements of the client with the corresponding technical achievements according to the technical requirements of the client;
searching the technical requirements of a client, inputting legal requirement keywords to be searched by the client, and inputting the requirement keywords to a technical query unit;
if the requirement key words are legal, similarity calculation is carried out on the requirement key words and the key words stored in the storage module, and K is { K ═ K { (K) 1，k2，k3，...，knIs a set of keywords, according to the formula:
Figure FDA0002564450990000021
wherein,
Figure FDA0002564450990000022
as a keyword kn1，kn2The degree of similarity to the set of keywords,
Figure FDA0002564450990000023
has a value range of [ -1, 1 [)]，
Figure FDA0002564450990000024
The larger the value of (A), the greater the similarity between the keyword and the keyword set, sim (k)n1kn，kn2kn) Represented in a set of keywords K, the keywords Kn1And a keyword kn2The similarity of (2);
when in use
Figure FDA0002564450990000025
Then, the requirement key word input by the client is shown as a legal requirement key word;
the technical result management unit is used for carrying out label classification on the technical results and classifying the technical results as labels according to the fields and key technologies of the technical results;
scoring the newly input technical result in each technical field respectively, selecting the technical field with the highest score as a technical field label of the technical result, simultaneously calculating the distribution frequency of key technologies in the technical result, and determining the key technology with the highest distribution frequency as a key technical label;
wherein, the technical field set accessed by the technical result is W ═ { W ═ W1，W2，W3，…WnAnd scoring the technical achievements in the technical field according to a formula:
Figure FDA0002564450990000031
wherein S isiFor technical field scoring, | Smax-WiI is the absolute value of the difference between the current highest score of the technical achievement and the current technical field;
calculating the key technology with the highest distribution frequency according to a formula:
Figure FDA0002564450990000032
Wherein E is the distribution frequency of technical achievements in the key technology, JnFor all key technologies, JdFor the key distribution frequency of the current technology, Jn-dKey distribution frequencies of the remaining technologies;
the technology query unit is used for a client to query and screen the required technology and select the technology meeting the intention according to the description of the recommended technology;
the technology tracking unit is used for tracking the technical requirements of the clients and the subsequent technical development, recording the subsequent implementation process of the technology and updating the technical state.
4. The intelligent big data-based retrieval matching system according to claim 1, wherein the storage module comprises a customer information storage unit and a technical information storage unit;
the client information storage unit is used for storing client information and comprises: the client name, the client contact information, the enterprise where the client is located, the client requirement and the client category;
the technical information storage unit is used for storing all technical information, including: technical name, technical field, technical inventor, technical company, key technical composition, technical point and current technical state;
wherein, the storage unit performs data update on the client information and the technical information at fixed time intervals as the technical state changes.
5. The big data-based intelligent data retrieval and matching system according to claim 3, wherein the activity information management module comprises an information publishing unit and a client feedback unit;
the information publishing unit is used for disclosing the latest information of the technology to the client, wherein the latest information comprises technical inventor information and technical specific information;
the customer feedback unit provides an evaluation service for the customer, the customer evaluates the credit of the system according to the information obtained by the technical service provided by the technical management module, the credit evaluation uses (a, b) to represent the credit score of the customer on the corresponding unit of the technical management module, and the credit evaluation is carried out according to a formula:
an＝∑u×an-1+s；
bn＝∑u×bn-1+1-s；
wherein u is the functional unit score under the technology management module, s represents the feedback evaluation to the technology management unit n, and s is a good score of 1.
6. The intelligent big data-based retrieval and matching method according to claim 1, comprising the following steps:
step S1, after the client enters the system, the basic information registration is carried out, and the client is classified according to the registration information;
step S2, managing the technical information, providing inquiry and screening technique according to the key words input by the client;
Step S3, storing the client information and the technical information, and updating the stored content according to the modification of the information;
and step S4, disclosing the latest technical information and providing a feedback path for the client to evaluate.
7. The big data based intelligent data retrieval and matching method according to claim 6, wherein the step S1 includes:
step S11, when the system user enters the system, the technical management is carried out to the system user to confirm the identity information of the system user;
step S12, dividing the customers into common customers, technical staff with technical achievements and technical demand staff, corresponding to different types of users, and providing corresponding technical services for the users;
and step S13, registering the basic information of the client information according to different categories, uploading the registration result to a storage module, and providing a communication mode and a technical communication path for the user when the clients of different categories need to perform technical communication.
8. The big data based intelligent data retrieval and matching method according to claim 6, wherein the step S2 includes:
step S21, searching the technical requirements of the customer, and matching the technical requirements of the customer with the corresponding technical achievements according to the technical requirements of the customer, including:
A client inputs legal requirement keywords to be searched, and inputs the requirement keywords into a technical query unit;
if the requirement key words are legal, similarity calculation is carried out on the requirement key words and the key words stored in the storage module, and K is { K ═ K { (K)1，k2，k3，...，knIs a set of keywords, according to the formula:
Figure FDA0002564450990000061
wherein,
Figure FDA0002564450990000062
as a keyword kn1，kn2The degree of similarity to the set of keywords,
Figure FDA0002564450990000063
has a value range of [ -1, 1 [)]，
Figure FDA0002564450990000064
The larger the value of (A), the greater the similarity between the keyword and the keyword set, sim (k)n1kn，kn2kn) Represented in a set of keywords K, the keywords Kn1And a keyword kn2The similarity of (2);
when in use
Figure FDA0002564450990000065
If so, indicating that the requirement keyword input by the customer is a legal requirement keyword, and entering step S23;
step S22, performing label classification on the technical result, and classifying the technical result as a label according to the field and the key technology of the technical result, wherein the label classification comprises the following steps:
scoring the newly input technical result in each technical field respectively, selecting the technical field with the highest score as a technical field label of the technical result, simultaneously calculating the distribution frequency of key technologies in the technical result, and determining the key technology with the highest distribution frequency as a key technical label;
wherein, the technical field set accessed by the technical result is W ═ { W ═ W 1，W2，W3，…WnAnd scoring the technical achievements in the technical field according to a formula:
Figure FDA0002564450990000066
wherein S isiFor technical field scoring, | Smax-WiI is the absolute value of the difference between the current highest score of the technical achievement and the current technical field;
calculating the key technology with the highest distribution frequency according to a formula:
Figure FDA0002564450990000071
wherein E is the distribution frequency of technical achievements in the key technology, JnFor all key technologies, JdFor the key distribution frequency of the current technology, Jn-dKey distribution frequencies of the remaining technologies;
step S23, according to the legal requirement key words of the client in the step S21, the technology required by the client is inquired and screened, and according to the description of the recommended technology, the technology meeting the intention is selected;
step S24, tracking the technical requirements of the customer and the subsequent technical development, recording the subsequent implementation progress of the technology, and updating the technical state.
9. The big data based intelligent data retrieval and matching method according to claim 6, wherein the step S3 includes:
step S31, storing the customer information;
step S32, all technical information is stored.
10. The big data based intelligent data retrieval and matching method according to claim 6, wherein the step S4 includes:
Step S41, the latest information of the technology is disclosed to the client;
step S42, the customer evaluates the credit of the system according to the information obtained by the technical service provided by the technical management module, the credit evaluation uses (a, b) to represent the credit rating of the customer to the corresponding unit of the technical management module, according to the formula:
an＝∑u×an-1+s；
bn＝∑u×bn-1+1-s；
wherein u is the functional unit score under the technology management module, s represents the feedback evaluation to the technology management unit n, and s is a good score of 1.
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