UFRGS@CLEF2008: Using association rules for cross-language information retrieval

Abstract

For UFRGS's participation on the TEL task at CLEF2008, our aim was to assess the validity of using algorithms for mining association rules to find mappings between concepts on a Cross-Language Information Retrieval scenario. Our approach requires a sample of parallel documents to serve as the basis for the generation of the association rules. The results of the experiments show that the performance of our approach is not statistically different from the monolingual baseline in terms of mean average precision. This is an indication that association rules can be effectively used to map concepts between languages. We have also tested a modification to BM25 that aims at increasing the weight of rare terms. The results show that this modified version achieved better performance. The improvements were considered to be statistically significant in terms of MAP on our monolingual runs. © 2009 Springer Berlin Heidelberg.