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.
Ali Mohammad Zareh Bidoki, James A. Thom