Instance-based collaborative filtering with fuzzy labels

In recommender systems, user ratings of items are often represented in terms of linguistic labels such as “fair” or “very good”. We investigate the potential of fuzzy sets as a means for modeling such labels, especially with regard to collaborative filtering algorithms. We propose a related fuzzy version of instance-based (memory-based) collaborative filtering and argue that it leads to more informative and accurate predictions. These claims are validated by means of two experimental studies.

• Type: Conference
• Year: 2003
• Where: EUSFLAT
• Authors: Eyke Hüllermeier
• Keywords: Collaborative filtering Algorithms, EUSFLAT 2003, EUSFLAT 2007, Recommender Systems, Related Fuzzy Version