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Federated search links multiple search engines into a single, virtual search system. Most prior research of federated search focused on selecting search engines that have the most relevant contents, but ignored the retrieval effectiveness of individual search engines. This omission can cause serious problems when federating search engines of different qualities.This paper proposes a federated search technique that uses utility maximization to model the retrieval effectiveness of each search engine in a federated search environment. The new algorithm ranks the available resources by explicitly estimating the amount of relevant material that each resource can return, instead of the amount of relevant material that each resource contains. An extensive set of experiments demonstrates the effectiveness of the new algorithm.
@inproceedings{1076051, author = {Luo Si and Jamie Callan}, title = {Modeling search engine effectiveness for federated search}, booktitle = {SIGIR '05: Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval}, year = {2005}, isbn = {1-59593-034-5}, pages = {83--90}, location = {Salvador, Brazil}, doi = {http://doi.acm.org/10.1145/1076034.1076051}, publisher = {ACM Press}, address = {New York, NY, USA}, }  ©2006 Association for Computing Machinery |
