Collaborative filtering for recommendation of areas in virtual worlds

Collaborative filtering (CF) is a class of recommendation methods that have been used in web contents such as video sites and electronic-commerce sites. To our knowledge, CF, however, has not been used in three-dimensional virtual worlds yet. In this paper, we verify the applicability of two state-of-the-art CF methods in a three-dimensional virtual world called Second Life (SL). Our experiment results on data from SL verify that CF methods can also be applied to area recommendation in virtual worlds. A discussion on which CF method should be used in this application domain is also given.