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Long-Term Learning for Web Search Engines

This paper considers how web search engines can learn from the successful searches recorded in their user logs.Document Transformation is a feasible approach that uses these logs to improve document representations.Existing test collections do not allow an adequate investigation of Document Transformation, but we show how a rigorous evaluation of this method can be carried out using the referer logs kept by web servers.We also describe a new strategy for Document Transformation that is suitable for long-term incremental learning.Our experiments show that Document Transformation improves retrieval performance over a medium sized collection of webpages.Commercial search engines may be able to achieve similar improvements by incorporating this approach...

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