Collaborative filtering uses a database about consumers’ preferences to make personal product recommendations and is achieving widespread success in both E-Commerce and Informat...
Kai Yu, Xiaowei Xu, Martin Ester, Hans-Peter Krieg...
Two major challenges in collaborative filtering are the efficiency of the algorithms and the quality of the recommendations. A variety of machine learning methods have been applie...
Customer preferences for products are drifting over time. Product perception and popularity are constantly changing as new selection emerges. Similarly, customer inclinations are ...
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...
Many scalable data mining tasks rely on active learning to provide the most useful accurately labeled instances. However, what if there are multiple labeling sources (`oracles...