RSmeetDB 2013 - 3rd International Workshop on Recommender Systems meet Databases - RSmeetDB '13

Recommender systems (RS) support users in personalized access to large collections of data. From a technical perspective, RS have their origins in different fields such as Information Filtering and Data Mining and they are built using a broad array of statistical methods and algorithms. E-Commerce and consumer decision support applications have been the traditional application domains of these types of systems.
However, the ever-increasing plethora of information supply due to cheap storage, the web revolution and user generated content applications, fuels the need for user-centric and context-aware information access and presentation in many more database application domains. The aim of this workshop is therefore to provide a forum for discussion and presentation of latest results that are on the intersection of database and recommender systems research. Relevant topics for submissions include, but are not limited to:
? Preference and context modeling in Databases
User and Community Modeling
Reputation and Trust Modeling
Context Modeling
? New Database Architectures integrating Recommender Systems
Rank integration
Resource recommendations
Learning to rank
Personal and social aspects in databases
Query recommendations
Personalized privacy preserving
New data and query models involving users and contexts
Scalability issues of databases and recommender systems
? Innovative applications of Recommender Systems in Databases
Preference elicitation from the Deep Web
Filtering based on data harvested from the Deep Web
Content-based recommendations from BLOBs
Reputation and trust management
Social recommender systems
Visual Analytics for Recommender Systems
? Semantics in Recommender Systems and Databases
Semantic Indexing and Recommender Systems
Semantic Annotation and Recommender Systems
Semantic Deep Web and Recommender Systems
Annotation and Indexing of the Deep Web for Recommender Systems
Distributed Semantic Indexing for Recommender Systems
Filtering of the Deep Web
? Evaluation methodologies and approaches
User-centric evaluation
Accuracy vs. error metrics
Evaluating for novelty, diversity and serendipity
Workshop Organizers:
Giovanni Semeraro
Department of Computer Science, University of Bari “Aldo Moro”, Italy
E-mail: semeraro-AT-di.uniba.it
Marco de Gemmis
Department of Computer Science, University of Bari "Aldo Moro", Italy
E-mail: degemmis-AT-di.uniba.it
Pasquale Lops
Department of Computer Science, University of Bari "Aldo Moro", Italy
E-mail: lops-AT-di.uniba.it
Markus Zanker
Institute of Applied Informatics, Alpen-Adria-Universität Klagenfurt, Austria
E-mail: markus.zanker-AT-aau.at