Machine learning for predicting user clicks in Webbased search offers automated explanation of user activity. We address click prediction in the Web search scenario by introducing...
Ding Zhou, Levent Bolelli, Jia Li, C. Lee Giles, H...
The transition of search engine users’ intents has been studied for a long time. The knowledge of intent transition, once discovered, can yield a better understanding of how diď...
Search engines are commercial entities that require revenue to survive. The most prevalent revenue stream for search engines is sponsored search, where content providers have sear...
We propose a model that leverages the millions of clicks received by web search engines to predict document relevance. This allows the comparison of ranking functions when clicks ...
In this paper we process and analyze web search engine query and click data from the perspective of the documents (URL’s) selected. We initially define possible document categor...