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...
Abstract. Data Mining, or Knowledge Discovery as it is also known, is becoming increasingly useful in a wide variety of applications. In the following paper, we look at its use in ...
Collaborative filtering and content-based filtering are two types of information filtering techniques. Combining these two techniques can improve the recommendation effectiveness....
We built a Web-based adaptive recommendation system for students to select and suggest architectural cases when they analyze "Case Study" work within the architectural de...
A common task of recommender systems is to improve customer experience through personalized recommendations based on prior implicit feedback. These systems passively track differe...