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CALL FOR PAPERS
9th Workshop on Intelligent Techniques for Web Personalization
& Recommender Systems
In conjunction with IJCAI 2011
July 16, 2011 - Barcelona, Spain
http://ls13-www.cs.uni-dortmund.de/homepage/itwp2011/index.shtml
Submission Deadline: April 20, 2011
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Web Personalization and recommendation systems have been steadily gaining
ground as essential components of today's Web based applications, including in
e-commerce and customer relationship management, in the delivery of business
services, in providing support for Web search and navigation, and in reducing
cognitive overload in information rich interactive social Web applications. The
proliferation of Web 2.0 applications has allowed users to go beyond simple
consumers of information and instead actively participate in shaping
collaborative environments in which users, resources, and user-provided content
are all networked together. This, in turn has increased the need for more
intelligent and personalized services that help users interact with and
navigate these complex information spaces. These include a new generation of
recommender systems that integrate multiple online channels, are more scalable,
are more adaptive, can better handle user interactivity, and are more adept at
user preference elicitation. To achieve this, such applications must rely on
intelligent techniques from AI, machine learning, Web mining, statistics, and
user modelling in order to leverage all available data, including the usage and
click-stream data (reflecting user behaviour), the content and meta-data
associated with resources, semantic domain knowledge, user profile information,
and underlying network structures. Efficient and intelligent techniques are
needed to mine this data for actionable knowledge, and to effectively use the
discovered knowledge to enhance the users' experience.
The aim of this workshop is to bring together researchers and practitioners
From Web Mining, Web Personalization, Recommender Systems, and User Modeling
communities in order to foster an exchange of information and ideas and to
facilitate a discussion of current and emerging topics related to the
development of intelligent Web personalization and Recommender Systems.
PAPER SUBMISSION AND PARTICIPATION
We invite original contributions in a variety of areas related to Web
personalization and Recommender Systems, including Data Modeling and
Integration; User Modeling and Preference Elicitation; Systems and
Architectures; Enabling Technologies; and Evaluation Methodologies, Metrics,
and Case Studies.
For a detailed list of topics, please see the workshop Web site:
http://ls13-www.cs.uni-dortmund.de/homepage/itwp2011/index.shtml
[email protected]
The format for submissions is the same as that of IJCAI 2011.
Please check the IJCAI 2011 website for the style files.
(http://ijcai-11.iiia.csic.es/calls/call_for_papers)
Papers should be no longer than 8 pages inclusive of all references and
figures. All papers must be submitted in PDF. All papers must be original, and
must not have not been published or submitted elsewhere. At least one author
for each accepted paper is expected to attend the workshop. In addition to the
standard long paper submission, we also invite short position or demo papers
that may be no longer than 4 pages.
Citable CEUR-WS (http://ceur-ws.org/) working notes will be produced containing
the papers presented at the workshop. Selected papers from the workshop may be
considered for expansion and inclusion in a special issue of a journal.
IMPORTANT DATES
* 20 Apr: Paper submission deadline
* 14 May: Author notification
* 05 Jun: Camera-ready versions due
* 16 Jul: Workshop held
WORKSHOP ORGANIZERS
Bamshad Mobasher, School of Computer Science, DePaul University, Chicago, USA
E-mail: [email protected]
Dietmar Jannach, Department of Computer Science Technische Universitat
Dortmund, Germany
E-mail: [email protected]
Sarabjot Singh Anand, Department of Computer Science, University of Warwick, UK
E-mail: [email protected]
Alfred Kobsa, University of California, Irvine, USA
E-mail: [email protected]
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