Abstract

With the explosive growth of the amount of information stored on computer networks such as the Internet, it is increasingly more difficult for information seekers to retrieve relevant information. Traditional document ranking functions employed by Internet search engines can be enhanced to improve the effectiveness of information retrieval (IR). This paper illustrates the design and development of a granular IR system to facilitate domain specific search. In particular, a novel computational model is designed to rank documents according the searchers’ specific granularity requirements. The initial experiments confirm that our granular IR system outperforms a classical vector-based IR system. In addition, user-based evaluations also demonstrate that our granular IR system is effective when compared with a well-known Internet search engine. Our research work opens the door to the design and development of the next generation of Internet search engines to alleviate the problem of information overload.

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