A construction method of a literature compilation life history question and answer system based on a knowledge graph

A construction method and knowledge graph technology, applied in neural learning methods, neural architecture, semantic tool creation, etc., can solve the problem of low efficiency of acquisition system, and achieve the effect of improving generalization performance and improving system function.

Active Publication Date: 2019-05-17
ZHEJIANG UNIV
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Problems solved by technology

[0006] The purpose of the present invention is to solve the shortcomings of the existing literary chronicle knowledge acquisition system such as low efficiency, and realize a literary chronicle question answering system based on knowledge graph

Method used

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  • A construction method of a literature compilation life history question and answer system based on a knowledge graph
  • A construction method of a literature compilation life history question and answer system based on a knowledge graph
  • A construction method of a literature compilation life history question and answer system based on a knowledge graph

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Embodiment

[0136] The specific steps for implementing this example will be described in detail below in conjunction with the method of the present technology, as follows:

[0137] 1. Design the ER diagram of the relational database mysql according to the field involved in the question and answer system; the ER diagram includes characters, locations, works, positions, non-relative relationships between characters, relationships between characters and places, relationships between characters and works, characters and de-authorization 20 tables such as relations; the person table contains 27 tables including id, name, surname, first name, gender, age of death, nationality, county, dynasty, year of birth, year of death, month of birth, month of death, date of birth, date of death, etc. Fields; filter, clean, and convert the structured data in the Chinese History Biography Database (CBDB); import the sorted data into the mysql database that has created the schema one by one.

[0138] 2. According ...

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Abstract

The invention discloses a construction method of a literature history question and answer system based on a knowledge graph, which comprises the following steps of constructing the knowledge graph ofa literature history vertical field by taking structural data related to Chinese literature history as a basis and combining a literature history ontology structure created from top to bottom; designing a semantic analysis framework which comprises two user question analysis modules characterized in that one module is based on regularization and rules, and the other module is based on a neural network; organizing the results obtained through problem analysis into corresponding SPARQL query statements, and searching the corresponding results for in the constructed knowledge graph; organizing the result as a reply, and returning the reply to the user; designing a webpage side and a WeChat official account service as a window for interaction between the system and a user; designing a user uses a log and feedback collection module, wherein the related data is used for iteratively training a neural network model, and the generalization capability of the model is enhanced. According to the present invention, the natural language query of a user can be directly processed, an accurate result is returned, and the method plays an important role in improving the knowledge acquisition efficiency, promoting Chinese culture research and the like.

Description

Technical field [0001] The invention relates to a question answering system, in particular to a method for constructing a literary chronicle question answering system based on a knowledge graph. Background technique [0002] Question answering system is an advanced form of information retrieval system, which can answer users’ questions in natural language; question answering system can meet users’ needs for fast and accurate information acquisition; unlike existing search engines, question answering system returns users It is no longer a sort of related documents based on keyword matching, but a precise natural language answer; Q&A systems can be divided into Q&A systems based on reading comprehension, Q&A systems based on community Q&A pairs, and Q&A systems based on knowledge graphs; [0003] The knowledge graph is mostly a graph structure composed of entities and relationships as basic units; based on such structured knowledge, the semantics of users’ natural language questions ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/332G06F16/36G06F17/27G06N3/04G06N3/08
Inventor 吴江琴黄诗磊庄越挺
Owner ZHEJIANG UNIV
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