User Modeling and User-Adapted Interaction
Adaptive interfaces and agents
The human-computer interaction handbook
Why we twitter: understanding microblogging usage and communities
Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis
Mediation of user models for enhanced personalization in recommender systems
User Modeling and User-Adapted Interaction
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TwitterRank: finding topic-sensitive influential twitterers
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Proceedings of the 19th international conference on World wide web
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ESWC'11 Proceedings of the 8th extended semantic web conference on The semanic web: research and applications - Volume Part II
Analyzing user modeling on twitter for personalized news recommendations
UMAP'11 Proceedings of the 19th international conference on User modeling, adaption, and personalization
Interweaving public user profiles on the web
UMAP'10 Proceedings of the 18th international conference on User Modeling, Adaptation, and Personalization
Semantically driven social data aggregation interfaces for Research 2.0
i-KNOW '11 Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies
Aggregated, interoperable and multi-domain user profiles for the social web
Proceedings of the 8th International Conference on Semantic Systems
Limosa: a system for geographic user interest analysis in Twitter
Proceedings of the 16th International Conference on Extending Database Technology
A Semantic Service-Oriented Platform for Integrated and Personalised Access to Sustainable Projects
Proceedings of International Conference on Information Integration and Web-based Applications & Services
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Twitter is today's most popular micro-blogging service on the Social Web. As people discuss various fresh topics, Twitter messages (tweets) can tell much about the current interests and concerns of a user. In this paper, we introduce TUMS, a Twitter-based User Modeling Service, that infers semantic user profiles from the messages people post on Twitter. It features topic detection and entity extraction for tweets and allows for further enrichment by linking tweets to news articles that describe the context of the tweets. TUMS is made publicly available as a Web application. It allows end-users to overview Twitter-based profiles in a structured way and allows them to see in which topics or entities a user was interested at a specific point in time. Furthermore, it provides Twitter-based user profiles in RDF format and allows applications to incorporate these profiles in order to adapt their functionality to the current interests of a user. TUMS is available via: http://wis.ewi.tudelft.nl/tums/