With the increasing storage capacity of personal computing devices, the problems of information overload and information fragmentation become apparent on users’ desktops. For the...
We propose a novel collaborative recommendation approach to take advantage of the information available in user-created lists. Our approach assumes associations among any two item...
We examine the problem of retrieving the top-m ranked items from a large collection, randomly distributed across an n-node system. In order to retrieve the top m overall, we must ...
This paper presents our bilingual question-answering system MUSCLEF. We underline the difficulties encountered when shifting from a mono to a cross-lingual system, then we focus o...
Traditional approaches to recommender systems have not taken into account situational information when making recommendations, and this seriously limits the relevance of the resul...