Pacific-Asia Workshop on Computational Intelligence and Industrial Application, IEEE (2008)
Dec. 19, 2008 to Dec. 20, 2008
With the development of Internet, more and more on-line information has become precious wealth that we can access to. High quality information is often stored in dedicated digital libraries. However, query system of most digital libraries based on keyword matching couldn’t make users satisfied. This paper presents an ontology-based digital library query system, whose capability goes far beyond simple key word based query. There are two important components in our system: query expansion and ontology extraction. In the proposed query system, we integrate “WorldNet” as the query expansion module to broaden the query scope, which leads to better recall rate for retrieval. A novel ontology inference algorithm was also proposed, which automatically constructs the ontology of the knowledge base for a specific query domain. With this domain specific ontology based knowledge representation, our query system is capable of human-like general semantic reasoning to disambiguate the ambiguous words and improve the precision of retrieval. We evaluate the proposed system on a large set of documents from 10 different subject domains. Experimental results demonstrate the effectiveness of our proposed system. Our system achieves on average 5% improvement compared with the traditional key word based search method.
Zhendong Niu, Xiaomei Xu, Feifei Zhang, "An Ontology-Based Query System for Digital Libraries", Pacific-Asia Workshop on Computational Intelligence and Industrial Application, IEEE, vol. 01, no. , pp. 222-226, 2008, doi:10.1109/PACIIA.2008.360