Enrichment for Web
نویسنده
چکیده
Search is among the most frequent activities on theWeb. However, the search activity still requires extraefforts in order to get satisfactory results. One of t hereasons is heterogeneous information resources andexponential increase of i nformation. The problem ofheterogeneity arises as result of di scipline specificlanguage used even in the domain specific documents.This particular problem we tackle in this paper. Wepropose an approach to construct semantic-linguisticfeature vectors that are used in search. The featurevectors are built based on domain semantics encodedin an ontology and enhanced by a relevant terminologyfrom the actual documents on t he Web. Semanticinformation from the ontologies is also used to expandthe user queries and the feature vectors are used tofilter and rank the retrieved documents. The value ofthis approach is twofold. First, it captures relevantsemantics from an ontology, and second, it accountsfor statistically significant collocations of ot her termsand phrases in relation to the ontology entities. In thispaper, we explain how these feature vectors areconstructed and what effect they have on s earchperformance.
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تاریخ انتشار 2011