The PRSAT 2010 proceedings are now available in the CEUR series.
User modeling, adaptation, and
personalization techniques have hit the mainstream. The explosion of
social network websites, on-line user-generated content platforms, and
the tremendous growth in computational power of mobile devices are
generating incredibly large amounts of user data, and an increasing desire
of users to "personalize" (their desktop, e-mail, news site, phone).
The potential value of personalization has become clear both as a commodity for the
benefit or enjoyment of end-users, and as an enabler of new or better
services –a strategic opportunity to enhance and expand businesses.
An exciting characteristic of recommender systems is that
they draw the interest of industry and businesses while posing
very interesting research and scientific challenges.
In spite of significant progress in the research community, and
industry efforts to bring the benefits of new techniques to end-users,
there are still important gaps that make personalization and adaptation
difficult for users. Research activities
still often focus on narrow problems, such as incremental accuracy
improvements of current techniques, sometimes with ideal hypotheses, or
tend to overspecialize on a few applicative problems (typically TV or
movie recommenders –sometimes simply because of the availability of
data). This restrains de facto the range of other applications where
personalization technologies might be useful as well.
Thus, we may have reached a good point to take a step back to seek
perspective in the research done in recommender systems. This workshop
contrives for a new uptake on past experiences and lessons learned. We
propose an analytic outlook on new research directions, or ones that
still require substantial research, with a special focus on their
practical adoption in working applications, and the barriers to be met
in this path.
This workshop aims at bringing the gap between academic researchers and
industry practitioners in the area of Recommender Systems. We are
interested both in research work that faces real industry problems, and
in industry cases that create research challenges.
The workshop will favor position papers, and
innovative approaches with original or compelling concepts that
stimulate discussions rather than the papers with incremental
contributions, even if fully evaluated.
|Topics of interests
This workshop is an
opportunity to bring together researchers and practitioners to discuss,
on one hand, the main lessons drawn from successes but also from
failures of recommender systems, and on the other hand, identify and
analyze the major research areas in recommendation and personalization
technologies that should be addressed in the future for a practical,
effective take-up of the needs of vendors, consumers, and technology
providers. Thus, topics of interest include, but are not limited to:
- Limits of recommender systems
- main bottlenecks, research dead ends and myths in
- missing technology pieces for wider adoption
- social (privacy, culture) issues
- Analytical view of personalization experiences
- case studies of recommender system implementations
- evaluation and user studies of recommender systems
- scalability in large recommender systems
- lessons learnt from your past experience
- obstacles to massive deployment of recommendation
solutions in industrial environments
- Recommender systems in broader systems
- place of recommender systems in complete systems
- killer application area
- Next needs in recommender systems
- new business models related to recommendation
- social and cultural impact of recommender systems
- new paradigms to provide recommendations
- new areas for recommendations
- users' expectations about future recommender systems
- beyond one-shot recommendations: recommendations of
sequences, goal-oriented recommendations, ...
The format of the workshop
will combine short paper presentations with open discussion sessions.
Papers will be grouped by topics allowing us to organize an open
discussion for every topic. Active participation will be expected and
formal conference-style presentations will be minimal. We invite two
kinds of submissions:
- Short papers / position papers reporting on lessons
learnt, concrete problems, new promising areas. The maximum length is 4
pages in the standard ACM SIG proceedings format.
- Long papers. The maximum length is 8 pages in the
standard ACM SIG proceedings format.
Submitted papers will be
evaluated according to their originality, technical content, style,
clarity, and relevance to the workshop. Each paper will be reviewed by
at least 3 independent referees.
Papers should be submitted
in PDF format. Submissions should be prepared according to the standard
SIG proceedings format. All submissions will be done electronically
via the PRSAT 2010 Web submission system: http://www.easychair.org/conferences/?conf=prsat2010.
At least one author of each
accepted paper must register for the workshop. Information about
registration will appear soon on the RecSys 2010 Web page: http://recsys.acm.org.
- Paper submission deadline: July 7, 2010
- Notification of acceptance/rejection: July 29, 2010
- Camera-ready version due: August 16, 2010
- Workshop: September 30, 2010
- David Bonnefoy, Pearltrees
- Makram Bouzid, Alcatel-Lucent Bell Labs
- Iván Cantador, Universidad Autónoma de Madrid
- José Carlos Cortizo, Universidad Europea de Madrid & BrainSins
- Alexander Felfernig, Graz University of Technology & ConfigWorks
- Ido Guy, IBM Haifa Research Lab
- Paola Hobson, Snell
- Rubén Lara, Telefónica I+D
- Kevin Mercer, BBC
- Andreas Nauerz, IBM Deutschland Research & Development GmbH
- Michael Papish, Media Unbound, Inc.
- Igor Perisic, LinkedIn Corporation
- Myriam Ribière, Alcatel-Lucent Bell Labs
- Neel Sundaresan, eBay Research Labs
- Marc Torrens, Strands, Inc.
- Andreas Töscher, Commendo Research & Consulting GmbH
- Xiaohui Xue, SAP