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...
People often find useful content on the web via social media. However, it is difficult to manually aggregate the information and recommendations embedded in a torrent of social ...
The influence of multimodal sources of input data to the construction of accurate computational models of user preferences is investigated in this paper. The case study presented...
In Web-based services of dynamic content (such as news articles), recommender systems face the difficulty of timely identifying new items of high-quality and providing recommendat...
Traditional DSL troubleshooting solutions are reactive, relying mainly on customers to report problems, and tend to be labor-intensive, time consuming, prone to incorrect resoluti...
Yu Jin, Nick G. Duffield, Alexandre Gerber, Patric...