Knowledge base system for bidding regulations and cases

Abstract

The invention discloses a knowledge base system for bidding regulations and cases, and relates to the technical field of information processing. Comprising a user terminal, an intelligent retrieval module, an intelligent review module, a personalized recommendation module, a bidding and tendering regulation and case knowledge base and a dynamic updating module. The user terminal is used for a user to log in the system and providing retrieval, review and recommendation operation interfaces for the user; the intelligent retrieval module is used for retrieving cases and bidding and tendering laws and regulations; the intelligent review module is used for reviewing the bidding book; the personalized recommendation module recommends related cases and bidding and tendering laws and regulations in a personalized manner according to the user roles, the belonging industries and browsing records; the bidding and tendering regulation and case knowledge base stores bidding and tendering regulations and classical cases related to the bidding and tendering regulations, and constructs a bidding and tendering regulation and classical case knowledge graph; and the dynamic updating module is used for updating the bidding and tendering regulation and case knowledge base. According to the method, deep association and accurate retrieval of laws and regulations and cases can be realized, and the learning efficiency of a user is improved.

Description

Technical Field

[0001] This invention relates to the field of information processing technology, and in particular to a knowledge base system for bidding regulations and cases. Background Technology

[0002] Bidding and tendering activities are a crucial part of the market economy, with extremely high compliance requirements. Furthermore, courts and finance departments at all levels publish numerous bidding and tendering dispute cases. With the continuous revision and improvement of bidding and tendering regulations, and the increasingly stringent compliance requirements in fields such as construction engineering and government procurement, traditional knowledge management methods are no longer adequate to meet the refined needs of the entire bidding and tendering process.

[0003] Currently, practitioners primarily rely on manual methods to retrieve and research relevant information, which presents the following technical problems: laws, regulations, and cases are scattered across different official websites and databases, lacking effective aggregation; traditional keyword search methods have low accuracy, failing to understand the true intent of user queries and making it difficult to quickly locate relevant information; there is a lack of deep connection between legal provisions and specific cases, making it difficult for users to intuitively understand the application and interpretation of legal provisions in practice; and automated compliance checks and risk warnings for bidding and tendering activities are impossible, relying on personal experience and thus posing high risks. Existing bidding and tendering management systems suffer from outdated legal provisions, high manual maintenance costs, and an inability to accurately link similar cases.

[0004] Therefore, proposing a knowledge base system of bidding regulations and cases to solve the difficulties existing in the current technology is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0005] In view of this, the present invention provides a knowledge base system of bidding regulations and cases, which can realize deep association and accurate retrieval of regulations and cases, and significantly improve the learning efficiency of users.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] A knowledge base system for bidding and tendering regulations and cases includes: a user terminal, an intelligent search module, an intelligent review module, a personalized recommendation module, a knowledge base for bidding and tendering regulations and cases, and a dynamic update module;

[0008] The user terminal is connected to the intelligent search module, the intelligent review module, and the personalized recommendation module; the intelligent search module, the intelligent review module, and the personalized recommendation module are connected to the bidding and tendering regulations and case knowledge base; the bidding and tendering regulations and case knowledge base is connected to the dynamic update module.

[0009] Optionally, in the aforementioned system, the user terminal is used for user login, providing users with an interface for searching, reviewing, and personalized recommendations; users can log in and verify their login through any of the following methods: a web portal, a mini-program, an app, or an API interface.

[0010] The above system, optionally, includes an intelligent search module for users to search for cases and bidding regulations in the bidding regulations and case knowledge base;

[0011] The natural language processing engine processes the natural language retrieved by the user to provide semantic search.

[0012] The aforementioned system may optionally include an intelligent review module, which performs intelligent review of user-uploaded bids, automatically identifies key clauses, marks potential conflict points, and generates a risk radar chart for the bids based on a knowledge base of bidding regulations and cases.

[0013] The system described above can optionally include a personalized recommendation module that recommends relevant bidding regulations and typical cases from the bidding regulations and case knowledge base based on the user's role, industry, and browsing history, thus planning a learning path for the user on bidding regulations.

[0014] The aforementioned system may optionally include a knowledge base for bidding regulations and cases, comprising: a bidding regulations storage unit, a case storage unit, and a knowledge graph unit.

[0015] The above system optionally includes a bidding and tendering regulations storage unit for storing structured text data of bidding and tendering regulations. The fields of the bidding and tendering regulations text data include: title, issuing authority, document number, issuing date, effective date, validity status, main text content, and chapter structure.

[0016] The case storage unit is used to store structured text data of classic cases related to bidding and tendering regulations. The case text data fields include: case title, case number, court of trial, judgment date, case summary, points of contention, judgment summary, legal basis, judgment result, and full text.

[0017] The knowledge graph unit processes the text data in the bidding regulations storage unit and the case storage unit using a natural language processing engine, extracts entities and relationships between entities from the bidding regulations and case text data, stores the relationships between entities in a graph structure, and constructs a structured knowledge graph.

[0018] The nodes in the knowledge graph include: legal nodes, case nodes, and entity nodes, and the edges represent the relationships between legal nodes, case nodes, and entity nodes.

[0019] The aforementioned system optionally includes a dynamic update module for updating the knowledge base of bidding and tendering regulations and cases, specifically:

[0020] We obtained revised texts of bidding regulations and classic case texts related to bidding regulations through web crawling, government bidding platform API interfaces, and manual uploads.

[0021] Text is cleaned and analyzed using natural language processing (NLP). NLP is used to perform entity recognition, extract semantic relationships, and generate tags and summaries.

[0022] The processed text is compared with a knowledge base of bidding and tendering regulations and cases to remove duplicates.

[0023] For the deduplicated text, a knowledge graph is constructed based on the relationships between entities;

[0024] The revised texts of bidding and tendering regulations, classic case texts, and knowledge graphs will be updated to the case library and the bidding and tendering regulations knowledge base.

[0025] As can be seen from the above technical solution, compared with the prior art, the present invention provides a knowledge base system for bidding and tendering regulations and cases, which has the following beneficial effects: The present invention can update the case library and the knowledge base for bidding and tendering regulations in real time, solving the problem of the timeliness of regulations in the field of bidding and tendering; through knowledge graph technology, it deeply associates scattered bidding and tendering regulations and cases to form an organic knowledge network, changing the state of information silos; it uses natural language processing (NLP) technology to achieve semantic-level retrieval and intelligent question answering, so that users do not need to memorize precise keywords to obtain accurate information, improving query efficiency and experience; by analyzing user behavior, it recommends the most relevant learning content for them, constructs personalized learning paths, and accelerates the accumulation of professional knowledge. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0027] Figure 1 This invention provides a structural diagram of a knowledge base system for bidding regulations and cases. Detailed Implementation

[0028] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0029] In this application, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. The terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0030] Reference Figure 1 As shown, this invention discloses a knowledge base system for bidding and tendering regulations and cases, including: a user terminal, an intelligent search module, an intelligent review module, a personalized recommendation module, a knowledge base for bidding and tendering regulations and cases, and a dynamic update module;

[0031] The user terminal is connected to the intelligent search module, the intelligent review module, and the personalized recommendation module; the intelligent search module, the intelligent review module, and the personalized recommendation module are connected to the bidding and tendering regulations and case knowledge base; the bidding and tendering regulations and case knowledge base is connected to the dynamic update module.

[0032] Furthermore, the user terminal is used for user login to the system, providing users with an interface for searching, reviewing, and personalized recommendations; users can log in and verify their login through any of the following methods: web portal, mini-program, APP, or API interface.

[0033] Furthermore, the intelligent search module is used by users to search for cases and bidding regulations in the bidding regulations and case knowledge base;

[0034] The natural language processing engine processes the natural language retrieved by the user to provide semantic search.

[0035] Specifically, through natural language processing, semantic retrieval that goes beyond keyword matching is provided. Users can search for the cases and bidding regulations they need through natural language. Users can also search the knowledge base of bidding regulations and cases through their user terminals and return the most relevant regulations and cases.

[0036] The intelligent retrieval module not only supports keyword search but also semantic expansion. For example, if a user searches for "discriminatory clauses," the system can link to various situations and related cases listed in Article 20 of the "Regulations for the Implementation of the Government Procurement Law." If a user's question "What performance requirements are reasonable?" is parsed into a query statement, the system can find the answer node in the graph and organize it into a natural language response.

[0037] Furthermore, the intelligent review module conducts intelligent reviews of user-uploaded bids, automatically identifies key clauses (such as qualification requirements and technical parameters) based on a knowledge base of bidding regulations and cases, marks potential conflict points, and generates a risk radar chart for the bids.

[0038] Furthermore, virtual bidding projects can be set up, allowing users to simulate writing bidding documents and tender documents. The system will automatically identify compliance risks and common errors based on built-in rules.

[0039] Furthermore, the personalized recommendation module recommends relevant bidding regulations and typical cases from the bidding regulations and case knowledge base based on the user's role, industry, and browsing history, thus planning a learning path for the user on bidding regulations.

[0040] Furthermore, the knowledge base for bidding and tendering regulations and cases includes: a storage unit for bidding and tendering regulations, a storage unit for cases, and a knowledge graph unit.

[0041] Furthermore, the bidding and tendering regulations storage unit is used to store structured text data of bidding and tendering regulations. The fields of the bidding and tendering law text data include: title, issuing authority, document number, date of issuance, effective date, validity status, main text content, and chapter structure; the bidding and tendering regulations data includes: national, ministerial, provincial and municipal bidding and tendering related laws, administrative regulations, departmental rules, local regulations, and normative documents.

[0042] The case storage unit is used to store structured text data of classic cases related to bidding and tendering regulations. The case text data fields include: case title, case number, court of trial, judgment date, case summary, points of contention, judgment summary, legal basis, judgment result, and full text content. The cases include: judgments from courts at all levels, administrative penalty decisions, and classic cases from the Ministry of Finance's government procurement information announcements.

[0043] The knowledge graph unit processes the text data in the bidding regulations storage unit and the case storage unit using a natural language processing engine, extracts entities and relationships between entities from the bidding regulations and case text data, stores the relationships between entities in a graph structure, and constructs a structured knowledge graph.

[0044] The nodes in the knowledge graph include: legal nodes, case nodes, and entity nodes, and the edges represent the relationships between legal nodes, case nodes, and entity nodes.

[0045] The aforementioned system optionally includes a dynamic update module for updating the knowledge base of bidding and tendering regulations and cases, specifically:

[0046] We obtained revised texts of bidding regulations and classic case texts related to bidding regulations through web crawling, government bidding platform API interfaces, and manual uploads.

[0047] The text is cleaned and analyzed using Natural Language Processing (NLP). NLP is used for entity recognition, semantic relation extraction, and tagging and summarization. Specifically, NLP includes: Entity Recognition (NER): automatically identifying key entities in the text (legal names, clauses, subjects, illegal acts, penalties, etc.); Relation Extraction (RE): extracting relationships between entities for knowledge graph construction; Text Classification and Tagging: automatically tagging cases, such as "Dispute Type: Invalid Bid," "Risk Level: High," "Related Legal Provision: Article 53 of the Bidding Law"; and Summary Generation: automatically generating core summaries and key points of judgments for each case.

[0048] The processed text is compared with a knowledge base of bidding and tendering regulations and cases to remove duplicates.

[0049] For the deduplicated text, a knowledge graph is constructed based on the relationships between entities;

[0050] The revised texts of bidding and tendering regulations, classic case texts, and knowledge graphs will be updated to the case library and the bidding and tendering regulations knowledge base.

[0051] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for system or system embodiments, since they are basically similar to method embodiments, the description is relatively simple, and relevant parts can be referred to the descriptions in the method embodiments. The systems and system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0052] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A knowledge base system for bidding and tendering regulations and cases, characterized in that, include: User terminal, intelligent search module, intelligent review module, personalized recommendation module, bidding and tendering regulations and case knowledge base and dynamic update module; The user terminal is connected to the intelligent search module, the intelligent review module, and the personalized recommendation module; the intelligent search module, the intelligent review module, and the personalized recommendation module are connected to the bidding and tendering regulations and case knowledge base; the bidding and tendering regulations and case knowledge base is connected to the dynamic update module.

2. The knowledge base system of bidding regulations and cases according to claim 1, characterized in that, The user terminal is used for users to log in to the system and provides users with an interface for searching, reviewing, and personalized recommendations; users can log in and verify their identity through any of the following methods: web portal, mini-program, APP, or API interface.

3. The knowledge base system of bidding regulations and cases according to claim 1, characterized in that, The intelligent search module is used by users to search for cases and bidding regulations in the bidding regulations and case knowledge base; The natural language processing engine processes the natural language retrieved by the user to provide semantic search.

4. The knowledge base system of bidding regulations and cases according to claim 1, characterized in that, The intelligent review module performs intelligent review of user-uploaded bids, automatically identifies key clauses, marks potential conflict points, and generates a risk radar chart for the bids based on a knowledge base of bidding regulations and cases.

5. The knowledge base system of bidding regulations and cases according to claim 1, characterized in that, The personalized recommendation module recommends relevant bidding regulations and typical cases from the bidding regulations and case knowledge base based on the user's role, industry, and browsing history, thus planning a learning path for the user on bidding regulations.

6. The knowledge base system of bidding regulations and cases according to claim 1, characterized in that, The knowledge base for bidding and tendering regulations and cases includes: a storage unit for bidding and tendering regulations, a storage unit for cases, and a knowledge graph unit.

7. The knowledge base system of bidding regulations and cases according to claim 6, characterized in that, The bidding and tendering regulations storage unit is used to store structured text data of bidding and tendering regulations. The fields of the bidding and tendering regulations text data include: title, issuing authority, document number, issuing date, effective date, validity status, main text content, and chapter structure. The case storage unit is used to store structured text data of classic cases related to bidding and tendering regulations. The case text data fields include: case title, case number, court of trial, judgment date, case summary, points of contention, judgment summary, legal basis, judgment result, and full text. The knowledge graph unit processes the text data in the bidding regulations storage unit and the case storage unit using a natural language processing engine, extracts entities and relationships between entities from the bidding regulations and case text data, stores the relationships between entities in a graph structure, and constructs a structured knowledge graph. The nodes in the knowledge graph include: legal nodes, case nodes, and entity nodes, and the edges represent the relationships between legal nodes, case nodes, and entity nodes.

8. The knowledge base system of bidding regulations and cases according to claim 1, characterized in that, The dynamic update module is used to update the knowledge base of bidding and tendering regulations and cases, specifically: We obtained revised texts of bidding regulations and classic case texts related to bidding regulations through web crawling, government bidding platform API interfaces, and manual uploads. Text is cleaned and analyzed using natural language processing (NLP). NLP is used to perform entity recognition, extract semantic relationships, and generate tags and summaries. The processed text is compared with a knowledge base of bidding and tendering regulations and cases to remove duplicates. For the deduplicated text, a knowledge graph is constructed based on the relationships between entities; The revised texts of bidding and tendering regulations, classic case texts, and knowledge graphs will be updated to the case library and the bidding and tendering regulations knowledge base.

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