- From: Giovanni Semeraro <giovanni.semeraro@uniba.it>
- Date: Mon, 22 Jul 2013 20:41:14 +0200
- To: <public-lod@w3.org>
- Message-ID: <00d701ce870b$0c095010$241bf030$@uniba.it>
[Apologies for possible multiple posts] --------------------------------------------- !!! SUBMISSION DEADLINE EXTENSION !!! --------------------------------------------- -------------------- CALL FOR PAPERS -------------------- RecSys'13 Workshop on Human Decision Making in Recommender Systems In conjunction with the 7th ACM Conference on Recommender Systems (RecSys '13) October 12, 2013, Hong Kong, China Workshop website: http://recex.ist.tugraz.at/RecSysWorkshop/ Submission deadline: August 1st, 2013 (*extended*) DESCRIPTION: Users interact with recommender systems to obtain useful information about products or services that may be of interest for them. But, while users are interacting with a recommender system to fulfill a primary task, which is usually the selection of one or more items, they are facing several other decision problems. For instance, they may be requested to select specific feature values (e.g., camera's size, zoom) as criteria for a search, or they could have to select feedback features to be critiqued in a critiquing based recommendation session, or they may need to select a repair proposal for inconsistent user preferences when interacting with a recommender. In all these scenarios, and in many others, users of recommender systems are facing decision tasks. The complexity of decision tasks, limited cognitive resources of users, and the tendency to keep the overall decision effort as low as possible is modeled by theories that conjecture "bounded rationality", i.e., users are exploiting decision heuristics rather than trying to take an optimal decision. Furthermore, preferences of users will likely change throughout a recommendation session, i.e., preferences are constructed in a specific decision environment and users may not fully know their preferences beforehand. Theories from decision psychology and cognitive psychology have already elaborated a number of methodological tools for explaining and predicting the user behavior in these scenarios, but recommender systems hardly integrate this knowledge in the computational model. The major goal of this workshop is to establish a platform for industry and academia to present and discuss new ideas and research results that are related to the topic of human decision making in recommender systems. We are specifically interested in the role of decision theories in advancing recommender systems research and applications. TOPICS: I) Theories, algorithms and applications - Decision theories in recommender systems (e.g., priming, framing, and decoy effects) - Trust inspiring recommendation (e.g., explanation-aware recommendation) - Persuasive recommendation (e.g., argumentation-aware recommendation) - The role of emotions in recommender systems (e.g., emotion-ware recommendation) - Mechanisms for effective group decision making (e.g., group recommendation heuristics) - Detection and avoidance of decision biases (e.g., in item presentations) - Personality-based recommender systems - Sequential decision making and selection - Applications of the above mentioned features II) User modeling and preference elicitation - Modeling user information search and decision making processes in recommender systems - Preference elicitation (e.g., eye tracking for automated preference detection) - Adaptive recommendation processes - Active approaches to preference elicitation III) User interfaces - User interfaces for decision making (e.g., decision strategies and user ratings) - User interfaces for group decision making (e.g., group decision making in e-tourism) - Explanations in Recommender Systems IV) Evaluation - User perceptions leading to the acceptance of recommendations - The role of diversity and serendipity for the acceptance of recommendations - Cultural differences (e.g., culture-aware recommendation) - Empirical studies and innovative metrics of system performance SUBMISSION INFORMATION: Submit either a full paper (8 pages) or a short paper (4-6 pages). Short papers may address an important problem for further research or describe a practical problem or an interesting lesson learned. In addition, we solicit proposals for short demonstrations (2-4 pages), and software demonstrations taking at most 15 minutes), emphasizing the original contribution, functionality or conceptual foundation of the system. All submissions will be handled electronically in PDF format. The submissions should follow the RecSys-2013 submissions guideline. Papers should be submitted via EasyChair submission system (https://www.easychair.org/conferences/?conf=decisionsrecsys13). If you have used EasyChair before, you may use your existing username and password. Otherwise please create a new EasyChair account. Each submission is refereed by at least two members of the program committee. Refereeing criteria are relevance to workshop topics, significance and novelty of the research, technical content, discussion on relation to previous work and clarity of presentation. A contribution submitted as a long paper may be accepted as a short paper, if the program committee considers it to be inadequate for a long paper but to present an important issue. At least one author of each accepted paper is required to attend the workshop to present the paper. WORKSHOP CO-CHAIRS: - Li Chen, Hong Kong Baptist University - Marco de Gemmis, University of Bari Aldo Moro, Italy - Alexander Felfernig, Graz University of Technology - Pasquale Lops, University of Bari Aldo Moro, Italy - Francesco Ricci, University of Bozen-Bolzano, Italy - Giovanni Semeraro, University of Bari Aldo Moro, Italy - Martijn Willemsen, Eindhoven University of Technology
Received on Monday, 22 July 2013 18:42:00 UTC