Improving the Relevance of Search Results

Synonymy & polysemy of natural languages together §with information overload are two main factors that §affect the relevance of Web hits. When §users submit a query, search engines usually return a §long list of hits with syntactic similarity. Users §are confronted with choosing a needle from a haystack relevant items from long lists of hits. This book §proposes an improved strategy for increasing the §relevance of Web search results via search term §disambiguation and ontological filtering. Results are §classified into an ontology, such as Open Directory §Project. Semantic characteristics of ontology §categories are represented by a category-document and §similarities of this and search results are evaluated §using a Vector Space Model. Users choose a category §to obtain only the search results classified under §the selected category. Experimental data show the §approach boosts the Web hits precision by more than §20%. The book should help shed some light on Web §searching and word sense disambiguation, and should §be useful to students and researchers in the fields §of information retrieval, text classification, and §data mining; or anyone else interested in Web §searching.