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基于语义理解的中文问答系统的设计与实现
作者:成思聪
来源:本站原创
更新时间:2013/11/18 14:26:00
正文:


                             (北京航空航天大学 软件学院北京市 100191)


摘要:随着互联网和信息检索技术的高速发展,近年来问答系统的应用日趋成熟,语义搜索引擎、语音助手等新产品大量涌现。配合语音识别技术,问答系统作为一种对现有搜索引擎的优化也能满足用户更丰富的信息检索需求。以Google为代表的第二代搜索引擎已经实现了对关键词相关的海量信息的快速检索,而这也带来了用户在海量搜索结果面前的“信息迷失”。希望通过自然语言描述,表达自己的查询需求,希望搜索服务系统能够理解用户意图,返回恰当的结果,因此更加符合用户检索需求的技术应运而生,语义搜索引擎、问答系统的研究成为当前自然语言处理领域中最有活力的方向之一。广域问答系统具有非常广泛的应用前景,例如网络答疑、公司客服等方面。本论文以研制广域的问答系统为目标,根据国内外问答系统的发展现状和所取得的成果,对中文问答系统及自然语言处理的相关的关键技术进行了较为深入的分析与探讨。经过技术选型,系统设计和实现,提供了一种良好的用户信息检索解决方案。
关键词:问答系统;问句处理;答案抽取;语义相似度。
Design and Implementation of Chinese Question-Answering System Based on Sematic Comprehension
SicongCheng
(School of Software, Beijing University of Aeronautics and Astronautics, Beijing 100191)
vheaven@163.com
Abstract:With the deeply development of internet and the rapid development of information retrieval technology in the world, the application of QA system matures, semantic search engines, voice assistant, and other new products are growing in large numbers. With voice recognition technology, answering system as an existing search engine optimization can meet user demand for richer information retrieval. Represented by Google's second-generation searching engine has achieved a mass of information on Keywords rapid retrieval, but it also brings the user in front of massive search results "message Lost". Hope that, through natural language and express their query requirements, they want the search service system to understand user intent, returns the appropriate result, and therefore more in line with user demand for technology emerges, semantic searching engines, QA system has become the NLP in the field one of the most dynamic direction. QA system has a very wide range of potential applications such as network answering, customer service and other aspects. In this thesis, the wide-area targeted QA system, according to the current development of domestic and abroad QA system and the results obtained on the Chinese QA system and analyses key techniques of Chinese QA and question processing deeply. After technology selection, system design and implementation,a good user information retrieval solution is provided.
Key words:QA system, Semantic similarity, Question processing, Answer extraction.

 

 


参考文献
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作者简介:
成思聪,北京航空航天大学软件学院硕士研究生,移动云计算专业,曾在爱立信中国研究院等多家

 
 
   
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