Optimising the parameters of ranking functions with respect to standard IR rank-dependent cost functions has eluded satisfactory analytical treatment. We build on recent advances ...
Michael J. Taylor, Hugo Zaragoza, Nick Craswell, S...
We describe a new family of topic-ranking algorithms for multi-labeled documents. The motivation for the algorithms stems from recent advances in online learning algorithms. The a...
Ranking search results is a fundamental problem in information retrieval. In this paper we explore whether the use of proximity and phrase information can improve web retrieval ac...
In recent years there has been considerable interest in analyzing random graph models for the Web. We consider two such models - the Random Surfer model, introduced by Blum et al....
Background: The MEDLINE database contains over 12 million references to scientific literature, ut 3/4 of recent articles including an abstract of the publication. Retrieval of ent...