Fuzzy Information Retrieval Model Based on Multiple Related Ontologies

– 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 preci...

• Type: Conference
• Year: 2008
• Where: ICTAI
• Authors: Maria Angelica A. Leite, Ivan L. M. Ricarte
• Keywords: Artificial Intelligence, ICTAI 2008, Information Retrieval, Knowledge Base, Query Expansion