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Research and Implementation of Chinese Question Answering System Based on Concept Graphs
Author: BoWenJuan
Tutor: ZhangLei
School: Northwestern University
Course: Applied Computer Technology
Keywords: Answering System Concept map FAQ set Noumenon Similarity
CLC: TP391.1
Type: Master's thesis
Year: 2010
Downloads: 119
Quote: 0
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Abstract
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Q \u0026 A system to natural language questions and to answer in the form of natural language , a new intelligent search engine . Compared to traditional search engines , answering system can better meet the requirements of the user's query , and retrieve the user needs more accurate answer . Answering system by the attention of many research institutions at home and abroad , and has developed a relatively mature English answering system , the study of Chinese question answering system which had been lacking . On this basis , the use of the concepts of the theory of Chinese question answering system technology research , and to achieve a Chinese question answering system based on the concept map . The system includes understanding of problems , information retrieval , answer extraction three modules , the specific contents are as follows : (1) in question understanding module, improved, using the method for classification of the traditional problems of doubt the word phrases and questions standard combination of classification problem , and feature words in the problem domain classification problem ; been studied using ontology resources concept map generation , and semantic - level analysis of the concept maps in the form of questions ; utilize ontologies extend from the the synonymous relationship and the relationship between two keywords . (2 ) in the information retrieval module FAQ library retrieval , If you can not find the answer in the FAQ database , turning to the Web retrieval and answer extraction module to extract answer ; FAQ database using three sources of knowledge to build and update , reverse indexing mechanism introduced in the FAQ database field classification of the problems in the FAQ database ; improved conceptual diagram of semantic similarity algorithm , and using this algorithm, the user questions and the questions in the FAQ database degree computation , using sentence similarity calculation the FAQ database based retrieval . ( 3 ) In the answer extraction module , named entity recognition technology and sentences the combination similarity calculation method for answer extraction . Finally, the above methods , the system test and analysis of experimental results verify the feasibility of the method used in this paper .
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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Text Processing
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