Hybrid User Preference Models for Second Life and OpenSimulator Virtual Worlds

Virtual world user models have similarities with hypertext system user models. User knowledge and preferences may be derived from the locations users visit or recommend. The models can represent topics of interest for the user based on the subject or content of visited locations, and corresponding location models can enable matching between users and locations. However, virtual worlds also present challenges and opportunities that differ from hypertext worlds. Content collection for a cross-world search and recommendation service may be more difficult in virtual worlds, and there is less text available for analysis. In some cases, though, extra information is available to add to user and content profiles enhance the matching ability of the system. In this paper, we present a content collection system for Second Life and OpenSimulator virtual worlds, as well as user and location models derived from the collected content. The models incorporate text, social proximity, and metadata attributes to create hybrid user models for representing user interests and preferences. The models are evaluated based on their ability to match content popularity and observed user behavior.