Analyses of multiple evidence combination
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
The NRRC reliable information access (RIA) workshop
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Fusion of effective retrieval strategies in the same information retrieval system
Journal of the American Society for Information Science and Technology
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In this paper, we study the use of a probabilistic fusion approach inspired from the probFuse algorithm [14]. Our fusing technique is based on queries that are classified using some automatically extracted linguistic features [11]. In this approach, performances which are estimated during a training phase are used as an indicator of the systems to fuse. The rank list of relevant documents provided by the systems are divided into segments and used in a training/testing process to detect the systems to fuse. Our fusion technique shows better performances than other fusion techniques like CombMNZ [10], ProbFuse [14] and Best_sys [11].