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

 

itwp2011@ls13.cs.uni-dortmund.de

 

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 

 

* 10 Apr:         Paper submission deadline

* 22 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: mobasher@cs.depaul.edu 


Dietmar Jannach, Department of Computer Science Technische Universitat Dortmund, Germany

E-mail: dietmar.jannach@udo.edu


Sarabjot Singh Anand, Department of Computer Science, University of Warwick, UK

E-mail: S.S.Anand@warwick.ac.uk 


Alfred Kobsa, University of California, Irvine, USA 

E-mail: kobsa@uci.edu