Long-Term Learning for Web Search Engines

摘要: 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 rigorous evaluation this method be carried out using referer kept by servers. We also describe new strategy for suitable long-term incremental learning.Our experiments improves retrieval performance over medium sized collection webpages.Commercial may able achieve similar improvements incorporating approach.