Italian monolingual information retrieval with PROSIT

Abstract

PROSIT (PRObabilistic Sifting of Information Terms) is a novel probabilistic information retrieval system that combines a term-weighting model based on deviation from randomness with information-theoretic query expansion. We report on the application of PROSIT to the Italian monolingual task at CLEF. We experimented with both standard PROSIT and with enhanced versions. In particular, we studied the use of bigrams and coordination level-based retrieval within the PROSIT framework. The main findings of our research are that (i) standard PROSIT was quite effective, with an average precision of 0.5116 on CLEF 2001 queries and 0.5019 on CLEF 2002 queries, (ii) bigrams were useful provided that they were incorporated into the main algorithm, and (iii) the benefits of coordination level-based retrieval were unclear. © Springer-Verlag Berlin Heidelberg 2003.