Collaborative Filtering (CF) algorithms, used to build webbased recommender systems, are often evaluated in terms of how accurately they predict user ratings. However, current eva...
Neal Lathia, Stephen Hailes, Licia Capra, Xavier A...
In this paper, we tackle the problem of top-N context-aware recommendation for implicit feedback scenarios. We frame this challenge as a ranking problem in collaborative filterin...
One of the key challenges in large information systems such as online shops and digital libraries is to discover the relevant knowledge from the enormous volume of information. Rec...
The explosive growth of the world-wide-web and the emergence of e-commerce has led to the development of recommender systems—a personalized information filtering technology use...
Tagging has emerged as a powerful mechanism that enables users to find, organize, and understand online entities. Recommender systems similarly enable users to efficiently navig...