An adaptive recommendation service seeks to adapt to its users, providing increasingly personalized recommendations over time. In this paper we introduce the \Fab" adaptive W...
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....
We address the task of learning rankings of documents from search engine logs of user behavior. Previous work on this problem has relied on passively collected clickthrough data. ...
Despite the recent advances in search quality, the fast increase in the size of the Web collection has introduced new challenges for Web ranking algorithms. In fact, there are sti...
Bruno M. Fonseca, Paulo Braz Golgher, Bruno P&ocir...
We are working on a project aimed at building next generation analyst support tools that focus analysts’ attention on the most critical and novel information found within the da...