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A Construction Method of Literary Chronicle Question Answering System Based on 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: 2020-11-24
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 Literary Chronicle Question Answering System Based on Knowledge Graph
  • A Construction Method of Literary Chronicle Question Answering System Based on Knowledge Graph
  • A Construction Method of Literary Chronicle Question Answering System Based on Knowledge Graph

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Embodiment

[0136] Below in conjunction with the method of this technology describe in detail the concrete steps that implement this example, as follows:

[0137] 1. Design the ER diagram of relational database mysql according to the fields involved in the question answering system; 20 tables such as relationships; the person table contains 27 tables including id, person name, surname, first name, gender, age at death, nationality, prefecture, dynasty, year of birth, year of death, month of birth, month of death, day of birth, day of death, etc. field; perform operations such as screening, cleaning, and conversion of the structured data in the Chinese Biography Database (CBDB); import the sorted data one by one into the mysql database with the created schema.

[0138] 2. According to the field involved in the question answering system and the created ER diagram, use the open source software protégé to establish the ontology structure of the literary chronicle; the ontology includes 14 mai...

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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 present invention relates to a question answering system, in particular to a method for constructing a question answering system for literary chronicles based on knowledge graphs. Background technique [0002] Question answering system is an advanced form of information retrieval system, which can answer questions raised by users in natural language; question answering system can meet users' needs for fast and accurate information; different from existing search engines, question answering system returns users It is no longer the sorting of relevant documents based on keyword matching, but the answers in the form of precise natural language; the question answering system can be divided into question answering systems based on reading comprehension, question answering systems based on community question and answer pairs, and question answering systems based on knowledge graphs; [0003] The knowledge graph is mostly a graph structure composed of ent...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/332G06F16/36G06F40/295G06F40/30G06N3/04G06N3/08
Inventor 吴江琴黄诗磊庄越挺
Owner ZHEJIANG UNIV
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