We propose a simple method for converting many standard measures of retrieval performance into metasearch algorithms. Our focus is both on the analysis of retrieval measures themselves and on the development of new metasearch algorithms. Given the conversion method proposed, our experimental results using TREC data indicate that systemoriented measures of overall retrieval performance (such as average precision) yield good metasearch algorithms whose performance equals or exceeds that of benchmark techniques such as CombMNZ and Condorcet. Categories and Subject Descriptors H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval – Retrieval models General Terms Theory, Algorithms, Experimentation Keywords Metasearch, Retrieval Evaluation
Javed A. Aslam, Virgiliu Pavlu, Emine Yilmaz