User Modeling and User-Adapted Interaction
The Benefit of Using Tag-Based Profiles
LA-WEB '07 Proceedings of the 2007 Latin American Web Conference
Cross-Domain Mediation in Collaborative Filtering
UM '07 Proceedings of the 11th international conference on User Modeling
Tagommenders: connecting users to items through tags
Proceedings of the 18th international conference on World wide web
Earthquake shakes Twitter users: real-time event detection by social sensors
Proceedings of the 19th international conference on World wide web
Personalized search by tag-based user profile and resource profile in collaborative tagging systems
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
ISWC'10 Proceedings of the 9th international semantic web conference on The semantic web - Volume Part I
Speak little and well: recommending conversations in online social streams
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Semantic enrichment of twitter posts for user profile construction on the social web
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 Trend and User Modeling for Personalized News Recommendation
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
DBpedia spotlight: shedding light on the web of documents
Proceedings of the 7th International Conference on Semantic Systems
Gumo: the general user model ontology
UM'05 Proceedings of the 10th international conference on User Modeling
A comparative study of users' microblogging behavior on sina weibo and twitter
UMAP'12 Proceedings of the 20th international conference on User Modeling, Adaptation, and Personalization
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In this paper, we present GeniUS, a generic topic and user modeling library for the Social Semantic Web that enriches the semantics of social data and status messages particularly. Given a stream of messages, it allows for generating topic and user profiles that summarize the stream according to domain- and application-specific needs which can be specified by the requesting party. Therefore, GeniUS can be applied in various application settings. In this paper, we analyze and evaluate GeniUS in six different application domains. Given users' status messages from Twitter, we investigate the quality of profiles that are generated by different GeniUS user modeling strategies for supporting various recommendation tasks ranging from product recommendations to more specific recommendations as required in book or software product stores. Our evaluation shows that GeniUS succeeds in inferring the semantic meaning of Twitter status messages. We prove that it can successfully adapt to a given domain and application context allowing for tremendous improvements of the recommendation quality when domain-specific semantic filtering is applied to remove noise from the profiles.