Natural language query translation and expansion in information retrieval

dc.contributor.authorIbrahim, Duraid Men_US
dc.date.accessioned2007-06-01T19:18:55Z
dc.date.available2007-06-01T19:18:55Z
dc.date.issued2000-01-01T00:00:00Zen_US
dc.degree.disciplineComputer Scienceen_US
dc.degree.levelMaster of Science (M.Sc.)en_US
dc.description.abstractQuery formulation and expansion have long been explored for enhancing query effectiveness and solving the word mismatch problem in information retrieval systems. Most of the approaches are statistical in nature. They are based on the occurrence frequency of words this thesis, we present a new approach based on natural language processing. Given a natural language query, our approach will translate a natural language query into a Boolean query that is better, in terms of retrieval effectiveness, than the original query. The terms in the Boolean query are assigned weights based on their contribution to the semantic of the query, which is determined by its occurrence frequency and its syntactic dependency within the query. Furthermore, the resulting weighted Boolean query can be further improved by expanding the query terms with synonyms in a very restrictive fashion. This process is fully automated and does not require human intervention. Experiments run for TREC-4 queries showed consistent improvement over standard information retrieval ranking methods.en_US
dc.format.extent4594991 bytes
dc.format.extent184 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.identifier.urihttp://hdl.handle.net/1993/2259
dc.language.isoengen_US
dc.rightsopen accessen_US
dc.titleNatural language query translation and expansion in information retrievalen_US
dc.typemaster thesisen_US
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