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Discovering Ranking Functions for Information Retrieval
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Author(s): Weiguo Fan (Virginia Polytechnic Institute and State University, USA)and Praveen Pathak (University of Florida, USA)
Copyright: 2005
Pages: 5
Source title:
Encyclopedia of Data Warehousing and Mining
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-59140-557-3.ch072
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Abstract
The field of information retrieval deals with finding relevant documents from a large document collection or the World Wide Web in response to a user’s query seeking relevant information. Ranking functions play a very important role in the retrieval performance of such retrieval systems and search engines. A single ranking function does not perform well across different user queries, and document collections. Hence it is necessary to “discover” a ranking function for a particular context. Adaptive algorithms like genetic programming (GP) are well suited for such discovery.
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