Automatic combination of multiple ranked retrieval systems
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Combining the evidence of multiple query representations for information retrieval
TREC-2 Proceedings of the second conference on Text retrieval conference
Analyses of multiple evidence combination
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
Predicting the effectiveness of Naïve data fusion on the basis of system characteristics
Journal of the American Society for Information Science
Modern Information Retrieval
Fusion Via a Linear Combination of Scores
Information Retrieval
Methods for ranking information retrieval systems without relevance judgments
Proceedings of the 2003 ACM symposium on Applied computing
Comparing Rank and Score Combination Methods for Data Fusion in Information Retrieval
Information Retrieval
A merging strategy proposal: The 2-step retrieval status value method
Information Retrieval
Automatic ranking of information retrieval systems using data fusion
Information Processing and Management: an International Journal
Performance prediction of data fusion for information retrieval
Information Processing and Management: an International Journal
Information Processing and Management: an International Journal
Advances in Multilingual and Multimodal Information Retrieval
CLEF 2008: ad hoc track overview
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
Overview of the ImageCLEFphoto 2008 photographic retrieval task
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
GeoCLEF 2008: the CLEF 2008 cross-language geographic information retrieval track overview
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
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Some recent works have shown that the "perfect" selection of the best IR system per query could lead to a significant improvement on the retrieval performance. Motivated by this fact, in this paper we focus on the automatic selection of the best retrieval result from a given set of results lists generated by different IR systems. In particular, we propose five heuristic measures for evaluating the relative relevance of each result list, which take into account the redundancy and ranking of documents across the lists. Preliminary results in three different data sets, and considering 216 queries, are encouraging. They show that the proposed approach could slightly outperform the results from the best individual IR system in two out of three collections, but that it could significantly improve the average results of individual systems from all data sets. In addition, the achieved results indicate that our approach is a competitive alternative to traditional data fusion methods.