Making large-scale support vector machine learning practical
Advances in kernel methods
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Using GPS to learn significant locations and predict movement across multiple users
Personal and Ubiquitous Computing
Adaptive web search based on user profile constructed without any effort from users
Proceedings of the 13th international conference on World Wide Web
Ranking web sites with real user traffic
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Activity-based serendipitous recommendations with the Magitti mobile leisure guide
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Characterizing user mobility in second life
Proceedings of the first workshop on Online social networks
Mobile Opportunistic Planning: Methods and Models
UM '07 Proceedings of the 11th international conference on User Modeling
PERSONAF: framework for personalised ontological reasoning in pervasive computing
User Modeling and User-Adapted Interaction
Second life: a social network of humans and bots
Proceedings of the 20th international workshop on Network and operating systems support for digital audio and video
TTI model: model extracting individual's curiosity level in urban spaces
Proceedings of the 8th ACM Conference on Designing Interactive Systems
Social network analysis of virtual worlds
AMT'12 Proceedings of the 8th international conference on Active Media Technology
Proceedings of the 7th ACM conference on Recommender systems
Hi-index | 0.00 |
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.