In this work we present topic diversification, a novel method designed to balance and diversify personalized recommendation lists in order to reflect the user's complete spec...
Cai-Nicolas Ziegler, Sean M. McNee, Joseph A. Kons...
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...
Online news reading has become very popular as the web provides access to news articles from millions of sources around the world. A key challenge of news websites is to help user...
Tagging plays an important role in many recent websites. Recommender systems can help to suggest a user the tags he might want to use for tagging a specific item. Factorization mo...
Many challenging tasks in sensor networks, including sensor calibration, ranking of nodes, monitoring, event region detection, collaborative filtering, collaborative signal proces...