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NCUEIR > College of Engineering > Department and Graduate Institute of Computer Science and Information Engineering > Proceedings > Item 987654321/11905

Please use this identifier to cite or link to this item: http://ir.ncue.edu.tw/ir/handle/987654321/11905

Title:	Developing a Fuzzy Search Engine Based on Fuzzy Ontology and Semantic Search
Authors:	Lai, Lien-Fu;Wu, Chao-Chin;Lin, Pei-Ying;Huang, Liang-Tsung
Contributors:	資訊工程學系
Keywords:	Fuzzy Search Engine;Fuzzy Ontology;Semantic Search
Date:	2011-06
Issue Date:	2012-07-02T02:27:30Z
Publisher:	IEEE
Abstract:	Most of existing search engines retrieve web pages by means of finding exact keywords. Traditional keyword-based search engines suffer several problems. First, synonyms and terms similar to keywords are not taken into consideration to search web pages. Users may need to input several similar keywords individually to complete a search. Second, traditional search engines treat all keywords as the same importance and cannot differentiate the importance of one keyword from that of another. Third, traditional search engines lack an applicable classification mechanism to reduce the search space and improve the search results. In this paper, we develop a fuzzy search engine, called Fuzzy-Go. First, a fuzzy ontology is constructed by using fuzzy logic to capture the similarities of terms in the ontology, which offering appropriate semantic distances between terms to accomplish the semantic search of keywords. The Fuzzy- Go search engine can thus automatically retrieve web pages that contain synonyms or terms similar to keywords. Second, users can input multiple keywords with different degrees of importance based on their needs. The totally satisfactory degree of keywords can be aggregated based on their degrees of importance and degrees of satisfaction. Third, the domain classification of web pages offers users to select the appropriate domain for searching web pages, which excludes web pages in the inappropriate domains to reduce the search space and to improve the search results.
Relation:	The 2011 IEEE International Conference on Fuzzy Systems, (FUZZ-IEEE 2011), June 27-30, 2011: 2684-2689
Appears in Collections:	[Department and Graduate Institute of Computer Science and Information Engineering] Proceedings

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