We evaluate three different relevance feedback (RF) algorithms, Rocchio, Robertson/Sparck-Jones (RSJ) and Bayesian, in the context of Web search. We use a target-testing experimen...
Vishwa Vinay, Kenneth R. Wood, Natasa Milic-Frayli...
Results clustering in Web Searching is useful for providing users with overviews of the results and thus allowing them to restrict their focus to the desired parts. However, the ta...
We present a general boosting method extending functional gradient boosting to optimize complex loss functions that are encountered in many machine learning problems. Our approach...
While searching the web, the user is often confronted by a great number of results, generally displayed in a list which is sorted according to the relevance of the results. Facing...
Nicolas Bonnel, Vincent Lemaire, Alexandre Cotarma...
The Stanford Power Browser project addresses the problems of interacting with the World-Wide Web through wirelessly connected Personal Digital Assistants (PDAs). These problems in...
Orkut Buyukkokten, Hector Garcia-Molina, Andreas P...