Long-term learning for web search engines

Abstract

This paper considers how web search engines can learn from the successful searches recorded in their user logs.D ocument Transformation is a feasible approach that uses these logs to improve document representations.E xisting 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.W e also describe a new strategy for Document Transformation that is suitable for long-term incremental learning.O ur experiments show that Document Transformation improves retrieval performance over a medium sized collection of webpages.C ommercial search engines may be abl..