Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
Communications of the ACM
CSCW research at GMD-FIT: from basic groupware to the social Web
ACM SIGGROUP Bulletin
Modern Information Retrieval
Machine Learning for User Modeling
User Modeling and User-Adapted Interaction
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User Modeling and User-Adapted Interaction
Mediation of user models for enhanced personalization in recommender systems
User Modeling and User-Adapted Interaction
Analyzing Museum Visitors' Behavior Patterns
UM '07 Proceedings of the 11th international conference on User Modeling
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Collaborative filtering recommender systems
The adaptive web
Content-based recommendation systems
The adaptive web
The adaptive web
Hybrid web recommender systems
The adaptive web
Social media recommendation based on people and tags
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Linkage, aggregation, alignment and enrichment of public user profiles with Mypes
Proceedings of the 6th International Conference on Semantic Systems
A visitor's guide in an active museum: Presentations, communications, and reflection
Journal on Computing and Cultural Heritage (JOCCH)
User model interoperability: a survey
User Modeling and User-Adapted Interaction
Proceedings of the 2012 ACM international conference on Intelligent User Interfaces
Augmenting user models with real world experiences to enhance personalization and adaptation
UMAP'11 Proceedings of the 19th international conference on Advances in User Modeling
Social filtering using social relationship for movie recommendation
ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part I
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In the past, classic recommender systems relied solely on the user models they were able to construct by themselves and suffered from the "cold start" problem. Recent decade advances, among them internet connectivity and data sharing, now enable them to bootstrap their user models from external sources such as user modeling servers or other recommender systems. However, this approach has only been demonstrated by research prototypes. Recent developments have brought a new source for bootstrapping recommender systems: social web services. The variety of social web services, each with its unique user model characteristics, could aid bootstrapping recommender systems in different ways. In this paper we propose a mapping of how each of the classical user modeling approaches can benefit from nowadays active services' user models, and also supply an example of a possible application.