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REDD 2014 : ACM RecSys 2014 Workshop on Recommender Systems Evaluation: Dimensions and Design

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Link: http://ir.ii.uam.es/redd2014
 
When Oct 1, 2014 - Oct 10, 2014
Where Foster City, CA, USA
Submission Deadline Jul 28, 2014
Notification Due Aug 21, 2014
Final Version Due Sep 5, 2014
 

Call For Papers

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Call for Papers - REDD 2014
International ACM RecSys Workshop on
Recommender Systems Evaluation: Dimensions and Design - REDD 2014
Foster City, Silicon Valley, CA, USA, October 2014
http://ir.ii.uam.es/redd2014
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* Submission deadline: 21 July 2014 *

== Scope ==

Evaluation is a cardinal issue in recommender systems; as in almost any other technical discipline, it highlights to a large extent the problems that need to be solved by the field and, hence, leads the way for algorithmic research and development in the community. Yet, in the field of recommender systems, there still exists considerable disparity in evaluation methods, metrics, and experimental designs as well as a significant mismatch between evaluation methods in the lab and what constitutes an effective recommendation for real users and businesses. This workshop aims at providing an informal forum to tackle such issues and move towards better understood and commonly agreed evaluation methodologies, allowing one to leverage the efforts and the workforce of the academic community on meaningful and relevant directions to real-world developments.

REDD 2014 places a specific focus, on the one hand, on the identification and measurement of different recommendation quality dimensions that go beyond the monolithic concept of simply matching user preferences. Novelty and diversity, for instance, have been recognized as key components of the utility of recommendations for users in real-world scenarios, with a direct positive effect on business performance. Considering the business perspective, performance metrics related to sales, revenues, and user engagement along the recommendation funnel should also be used. Additionally, from an engineering point of view, aspects such as efficiency, scalability, robustness, and user interface design are typically major concerns; often prioritized over the effectiveness of the internal algorithms at the core of the system. On the other hand, once a relevant target quality has been defined, a clear evaluation protocol should be specified in detail and agreed upon, allowing for the comparison, replicability and reproducibility of the results and experiments by different authors and enabling incremental contributions.

REDD 2014 aims at gathering researchers and practitioners interested in better understanding the unmet needs of the field in terms of evaluation methodologies and experimental practices. The main goal of this workshop is to provide an informal setting for discussing and exchanging ideas, experiences, and viewpoints. REDD seeks to identify and better understand the current gaps in recommender system evaluation methodologies, help lay directions for progress in addressing them, and foster the consolidation and convergence of experimental methods and practices.

== Topics ==

We invite the submission of papers reporting original research, studies, advances, experiences, or work in progress in the scope of recommender system utility evaluation. The topics the workshop seeks to address include –though need not be limited to– the following:

* Recommendation quality dimensions
- Effective accuracy, ranking quality
- Novelty, diversity, unexpectedness, serendipity
- Utility, gain, cost, risk, benefit
- Robustness, confidence, coverage, ease of use, persuasiveness, etc.
* Matching metrics to tasks, needs, and goals
- User satisfaction, user perception, human factors
- Business-oriented evaluation
- Multiple objective optimization, user engagement
- Quality of service, quality of experience
* Evaluation methodology and experimental design
- Definition and evaluation of new metrics, studies of existing ones
- Adaptation of methodologies from related fields: IR, Machine Learning, HCI, etc.
- Evaluation theory
* Practical aspects of evaluation
- Offline and online experimental approaches
- Simulation-based evaluation
- Datasets and benchmarks
- Validation of metrics
- Efficiency and scalability
- Open evaluation platforms and infrastructures

== Submission ==

Two submission types are accepted: technical papers up to 6 pages long, and position papers up to 3 pages. Each paper will be evaluated by at least two reviewers from the Programme Committee. The papers will be evaluated for their originality, contribution significance, soundness, clarity, and overall quality. Within a required quality standard, position papers will be evaluated based on the presentation of new perspectives and insights, and their potential for provoking thoughts and stimulating discussion.

All submissions shall adhere to the standard ACM SIG proceedings format: http://www.acm.org/sigs/publications/proceedings-templates. The accepted papers will be published in the CEUR Proceedings series.

Submissions shall be sent as a pdf file through the online submission system now open at: http://www.easychair.org/conferences/?conf=redd2014.

== Important dates ==

Paper submission deadline: 28 July 2014
Author notification: 21 August 2014
Camera ready version due: 3 September 2014
REDD 2014 workshop: 10 October 2014

== Programme Committee ==

Marcel Blattner, Univ. of Applied Sciences, Switzerland
Iván Cantador, Universidad Autónoma de Madrid, Spain
Charles Clarke, University of Waterloo, Canada
Arjen de Vries, CWI, The Netherlands
Juan Manuel Fernández, Universidad de Granada, Spain
Zeno Gantner, Nokia, Germany
Ido Guy, IBM Haifa Research Lab, Israel
Juan Huete, Universidad de Granada, Spain
Kris Jack, Mendeley, UK
Dietmar Jannach, University of Dortmund, Germany
Jaap Kamps, University of Amsterdam, Netherlands
Alexandros Karatzoglou, Telefonica Research, Spain
Bart Knijnenburg, University of California, Irvine, USA
Till Plumbaum, TU Berlin, Germany
Filip Radlinski, Microsoft, Canada
Alan Said, TU Delft, Netherlands
Yue Shi, TU Delft, The Netherlands
Fabrizio Silvestri, Yahoo!, Spain
David Vallet, Google Inc., Australia
Jun Wang, University College London, UK
Xiang-Jun Wang, Netflix
Xiaoxue Zhao, University College London, UK

== Organizers ==

Panagiotis Adamopoulos, New York University, USA
Alejandro Bellogín, Universidad Autónoma de Madrid, Spain
Pablo Castells, Universidad Autónoma de Madrid, Spain
Paolo Cremonesi, Politecnico di Milano, Italy
Harald Steck, Netflix, USA

Contact email: redd2014@easychair.org

More info at: http://ir.ii.uam.es/redd2014

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