Combination of documents features based on simulated click-through data

Abstract

Many different ranking algorithms based on content and context have been used in web search engines to find pages based on a user query. Furthermore, to achieve better performance some new solutions combine different algorithms. In this paper we use simulated click-through data to learn how to combine many content and context features of web pages. This method is simple and practical to use with actual click-through data in a live search engine. The proposed approach is evaluated using the LETOR benchmark and we found it is competitive to Ranking SVM based on user judgments. © Springer-Verlag Berlin Heidelberg 2009.