Term proximity and data mining techniques for information retrieval systems

Abstract

Term clustering based on proximity measure is a strategy leading to efficiently yield documents relevance. Unlike the recent studies that investigated term proximity for improving matching function between the document and the query, in this work the whole process of information retrieval is thoroughly revised on both indexing and interrogation steps. Consequently, an Extended Inverted file is built by exploiting the term proximity concept and using data mining techniques. Then three interrogation approaches are proposed, the first one uses query expansion, the second one is based on the Extended Inverted file and the last one hybridizes retrieval methods. Experiments carried out on OHSUMED demonstrate the effectiveness and efficiency of our approaches compared to the traditional one. © 2013 Springer-Verlag.