个人信息Personal Information
教授
硕士生导师
性别:男
毕业院校:吉林大学
学位:博士
所在单位:信息管理与信息系统研究所
学科:信息管理与电子政务
办公地点:管理楼518
电子邮箱:ywang@dlut.edu.cn
An ontology evolving-driven personalized semantic search system
点击次数:
论文类型:期刊论文
发表时间:2016-05-01
发表刊物:ICIC Express Letters
收录刊物:EI、Scopus
卷号:10
期号:5
页面范围:1101-1108
ISSN号:1881803X
摘要:Semantic search based on ontology is a relatively new promising search technology in Web search. The quality of search result is crucial for the success of a search system and depends mainly on the domain ontology in semantic search. However, the domain ontologies usually fail to be updated in time and even in some cases still stay in the initial state that does not contain enough semantics to provide the powerful support for semantic search as the Web evolves continuously. As a result, the quality of search result was often poor. This paper proposes an ontology evolving-driven semantic search system that combines the automatic ontology evolution with semantic search. The aim of this modification is to efficiently enhance the performance of the semantic search by periodically automatic ontology evolution, which can enrich the domain ontology by adding more semantics into it. Furthermore, an algorithm of personalized ranking based on ontology is presented in this paper in order to ensure achieving the high-quality ranking results. The performance of the proposed system is evaluated with three experiments, and the experimental results show that the improved semantic search system has a much better performance than the one without ontology evolution. ? 2016 ICIC International.