2013 Conference on User Modeling, Adaptation and Personalization
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The 21st Conference on User Modeling, Adaptation and Personalization (UMAP 2013) will be held from June 10 to June 14 in Rome, Italy. Recommender systems are explicitly mentioned in the call for papers, both as an application domain and as purpose.
External links
Papers
A list of papers that mention Recommender Systems / Collaborative Filtering / Personalization in their title:
- A Framework for Trust-based Multidisciplinary Team Recommendation. Lorenzo Bossi, Stefano Braghin, Anwitaman Datta and Alberto Trombetta.
- Combining Collaborative Filtering and Semantic Similarity for Expertise Recommendations in Social Websites. Alexandre Spaeth and Michel C. Desmarais.
- Cross-Domain Recommendation in a Cold-Start Context: The impact of User Profile Size on the Quality of Recommendation. Shaghayegh Sahebi and Peter Brusilovsky.
- Exploiting the Semantic Similarity of Contextual Situations for Pre-Filtering Recommendations. Victor Codina, Francesco Ricci and Luigi Ceccaroni.
- Interaction Based Content Recommendation in Online Communities. Surya Nepal, Cecile Paris, Payam Aghaei Pour, Jill Freyne and Sanat Kumar Bista.
- Opinion-Driven Matrix Factorization for Rating Prediction. Stefan Pero and Tomas Horvath.
- Personalized Access to Scientific Publications: From Recommendation to Explanation. Dario De Nart, Felice Ferrara and Carlo Tasso.
- Predicting Users’ Preference from Tag Relevance. Tien Nguyen and John Riedl.
- Recommendation for New Users with Partial Preferences via Incorporating Product Reviews. Feng Wang, Weike Pan and Li Chen.
- Recommendation with Differential Context Weighting. Yong Zheng, Robin Burke and Bamshad Mobasher.
- Recommending Topics for Web Curation. Zurina Saaya, Markus Schaal, Rachael Rafter and Barry Smyth.
- Scrutable User Models and Personalised Item Recommendation in Mobile Lifestyle Applications. Rainer Wasinger, James Wallbank, Luiz Pizzato, Judy Kay, Bob Kummerfeld, Matthias Böhmer and Antonio Krüger.
- What Recommenders Recommend — An Analysis of Accuracy, Popularity, and Sales Diversity Effects. Dietmar Jannach, Lukas Lerche, Fatih Gedikli and Geoffray Bonnin.
- [Workshop] EMPIRE Emotions and Personality in Personalized Services (EMPIRE) (Marko Tkalčič, Nadja De Carolis, Marco de Gemmis, Ante Odid, Andrej Košir)
- [Workshop] GroupRS Group Recommender Systems: Concepts, Technology, Evaluation (Tom Gross, Judith Masthoff, Christoph Beckmann)
- [Workshop] PALE Personalization Approaches in Learning Environments (Milos Kravcik, Olga C. Santos, Jesus G. Boticario, Diana Pérez-Marín)
- [Workshop] PEGOV Personalization in eGovernment Services and Applications (Nikos Loutas, Fedelucio Narducci, Matteo Palmonari, Cécile Paris)
- [Workshop] TRUM Trust, Reputation and User Modeling (Surya Nepal, Julita Vassileva, Cécile Paris, Jie Zhang)