An Automated Domain-Specific Answer Ontology Construction

Wei-Min Ko, Huan-ChungLi
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引用次数: 0

Abstract

Recently, with the fast development of interactive information sharing on the internet, the query-oriented answer search services are more and more popular, such as Yahoo Answers, Google Answers and so on. Their common advantages are high precision, domain-specific search, clear format, etc. However towards domain-specific search, people usually are unable to determine suitable concept terms as queries to submit on account of their lack of domain knowledge. In this paper, we propose an approach for constructing a domain-specific answer ontology automatically in respect of Chinese queries to solve the said problem. First, queries and their answers are collected from a web search space. Second, for extracting implicated concept terms from collected queries and answers, the CKIP system is utilized to make a Chinese part-of-speech tagging procedure to segment. Thirdly, use a similarity measure to converge duplicate queries with their corresponding answers and take fuzzy clustering method and degree of membership to describe the relationships between converged queries and their corresponding answers. Finally, to generate a domain-specific ontology is based on an improved hierarchical agglomerative clustering algorithm to hierarchically group queries.
一个自动化的领域特定答案本体构建
近年来,随着互联网上交互式信息共享的快速发展,面向查询的答案搜索服务越来越受欢迎,如Yahoo Answers、b谷歌Answers等。它们的共同优点是精度高、搜索特定于领域、格式清晰等。然而,对于特定领域的搜索,由于缺乏领域知识,人们往往无法确定合适的概念词作为提交的查询。在本文中,我们提出了一种针对中文查询自动构建特定领域答案本体的方法来解决上述问题。首先,从网络搜索空间收集查询及其答案。其次,为了从收集的查询和回答中提取隐含概念术语,利用CKIP系统编写汉语词性标注程序进行分词。第三,采用相似度度量将重复查询与其对应的答案收敛,并采用模糊聚类方法和隶属度描述收敛查询与其对应的答案之间的关系。最后,基于改进的分层聚类算法对查询进行分层分组,生成特定领域的本体。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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