Click data captures many users’ document preferences for a query and has been shown to help significantly improve search engine ranking. However, most click data is noisy and of...
This paper is concerned with relevance ranking in search, particularly that using term dependency information. It proposes a novel and unified approach to relevance ranking using ...
Learning ranking (or preference) functions has been a major issue in the machine learning community and has produced many applications in information retrieval. SVMs (Support Vect...
The leading web search engines have spent a decade building highly specialized ranking functions for English web pages. One of the reasons these ranking functions are effective is...
Methods for ranking World Wide Web resources according to their position in the link structure of the Web are receiving considerable attention, because they provide the first e...