DMCA
Fuzzy Information Retrieval Model Based on Multiple Related
BibTeX
@MISC{Angelica_fuzzyinformation,
author = {Maria Angelica and A. Leite and Ivan L. M. Ricarte (orientador},
title = {Fuzzy Information Retrieval Model Based on Multiple Related},
year = {}
}
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Abstract
Abstract – With the World Wide Web popularity the information retrieval area has a new challenge intending to retrieve information resources by their meaning by using a knowledge base. Nowadays ontologies are being used to model knowledge bases. To deal with knowledge subjectivity and uncertainty fuzzy set theory techniques are employed. Preceding works encode a knowledge base using just one ontology. But a document collection can deal with different domain themes, expressed by distinct ontologies. In this work a way of knowledge organization and representation as multiple related ontologies was investigated and a method of query expansion was developed. The knowledge organization and the query expansion method were integrated in the fuzzy model for information retrieval based on mutiple related ontologies. The model performance was compared with another fuzzy-based approach for information retrieval and with the Apache Lucene search engine. In both cases the proposed model improves the precision and recall measures.
Keyphrases
fuzzy information retrieval model knowledge base multiple related information retrieval knowledge organization document collection new challenge intending distinct ontology fuzzy-based approach theory technique information resource multiple related ontology query expansion method world wide web popularity apache lucene search engine mutiple related ontology model performance uncertainty fuzzy information retrieval area fuzzy model recall measure query expansion different domain theme knowledge subjectivity
