IJCAI 2003 Workshop on Intelligent Techniques for Web Personalization (ITWP '03)

IJCAI 2003 Workshop on Intelligent Techniques for Web Personalization (ITWP 
'03) 
Monday, August 11, 2003 
Acapulco, Mexico
http://maya.cs.depaul.edu/~mobasher/itwp03/

Overview 
The continued explosion in the amount of content and the number for information 
sources available online is making the need for effective personalized content 
delivery more acute. This has resulted in a renewed interest in Web 
personalization as an indispensable tool for Web-based organizations. 
Personalization can be defined as any action that tailors the Web experience to 
a particular user, or set of users. The experience can be something as casual 
as browsing a Web site or as (economically) significant as trading stocks or 
purchasing a car. The actions can range from simply making the presentation 
more pleasing to anticipating the needs of a user and providing customized and 
relevant information. To achieve effective personalization, organizations must 
rely on all available data, including the usage and click-stream data 
(reflecting user behaviour), the site content, the site structure, domain 
knowledge, as well as user demographics and profiles. In addition, efficient an!
 d intelligent techniques are needed to mine this data for actionable 
knowledge, and to effectively use the discovered knowledge to enhance the 
users' Web experience. These techniques must address important challenges 
emanating from the size and the heterogeneous nature of the data itself, as 
well as the dynamic nature of user interactions with Web sites, especially in 
e-commerce applications. These challenges include the scalability of the 
personalization solutions, data integration, and successful integration of 
techniques from machine learning, information retrieval and filtering, 
databases, knowledge representation, data mining, text mining, statistics, and 
human-computer interaction. Throughout the history of the Web, AI has continued 
to play an essential role in the development of Web-based information systems, 
and now it is believed that e-commerce and specifically personalization will 
prove to be the "killer-app" for AI. E-commerce and Web information systems are 
ric!
 h sources of difficult problems and challenges for AI researchers. Thi
s workshop intends to bring together researchers and practitioners to foster an 
exchange of information and ideas, and to facilitate a discussion of current 
and emerging topics related to Web Intelligence. Web Intelligence exploits AI 
and advanced information technology on the Web and Internet, in order to gain 
business intelligence and to assist users. The goal of the workshop is to 
stimulate the future development of new models, methodologies, and tools for 
Web intelligence, including effective and scalable Web-based personalization 
solutions and recommender systems. 

Topics 
Original contributions are solicited in the following areas:  
- Data and Knowledge Modeling, Integration and Management  
        - Using domain knowledge for more effective personalization  
        - Data models for Web usage, content, and structure data  
        - Data integration across multiple channels  
        - Generation and updating of user profiles  
        - Cognitive models for Web navigation and e-commerce interactions  
        - The role of user context 
- Enabling Technologies  
        - Machine learning and data mining in personalization  
        - Text mining techniques for content-based filtering  
        - Semantic Web mining  
        - Privacy preserving personalization  
        - Standards for data and knowledge modeling (e.g., PMML, RDF, CPEX, 
DAML)  
- Quality of Service in Personalization  
        - Techniques for improving online data quality  
        - Evaluation of recommendation engines  
        - Metrics for personalization effectiveness  
- Systems and Architectures  
        - Frameworks and systems for scalable collaborative filtering  
        - Agents for intelligent browsing and navigation  
        - Intelligent question answering systems  
        - Adaptive hypertext systems  
        - Hybrid Recommendation Systems  

Submission Instructions 
A title and abstract of the paper must be submitted by February 28, 2003. Full 
papers must be submitted by 9pm GMT March 7, 2003. All submissions must be made 
electronically to ss.anand-X0TtZdlT4kGdZ29H/IFGnA@xxxxxxxxxxxxxxxx Authors are 
required to submit a version of their full papers in camera-ready format as 
prescribed by the IJCAI web site. Complete instructions for formatting the 
paper will be available at the IJCAI-03 Web site (<http://www.ijcai-03.org>) by 
December 1, 2002. Papers should be no more than 8 pages inclusive of all 
references and figures. All papers must be submitted in either PDF (preferred) 
or postscript. It is the responsibility of the authors to ensure that the 
submitted papers print correctly on a variety of printers. If any special fonts 
are used, they must be included in the submission. All papers must be original, 
and have not been submitted elsewhere.  
Note: Participants are expected to register for the main IJCAI conference in 
addition to the workshop. 

Important Dates and Deadlines 
Abstract Submission: February 28, 2003 
Full Paper Submission: March 7, 2003 
Notification of Acceptance: March 28, 2003 
Camera Ready Papers Due: May 23, 2003 

Organizing Committee 
Bamshad Mobasher (Co-Chair) School of Computer Science, Telecommunication, and 
Information Systems, DePaul University, 243 S. Wabash Ave. Chicago, IL, 60604, 
USA mobasher-3OFKzk7aIKxkZI0wD67Jjg@xxxxxxxxxxxxxxxx   
Sarabjot Singh Anand (Co-Chair) NIKEL, Faculty of Informatics, University of 
Ulster, Northern Ireland, UK , ss.anand-X0TtZdlT4kGFxr2TtlUqVg@xxxxxxxxxxxxxxxx 
 

Program Committee 
Robert Cooley, KXEN., USA  
Asuman Dogac, METU, Turkey  
C. Lee Giles, Pennsylvania State University, USA  
Mark Levene, Birkbeck University of London, UK  
Jiming Liu, Hong Kong Baptist University, Hong Kong  
Maurice Mulvenna, NIKEL, Faculty of Informatics, University of Ulster, Northern 
Ireland, UK  
Dunja Mladanic, Josef Stefan Institute, Slovenia  
Enric Plaza, Institut d'Investigació en Intel.ligència Artificial, Catalonia 
(Spain)  
Francesco Ricci, ITC-irst, Italy  
Barry Smyth, University College Dublin, Ireland  
Myra Spiliopoulou, Leipzig Graduate School of Management, Germany  
Jaideep Srivastava, University of Minnesota, USA  
Alex Tuzhilin, Stern School of Business, New York University, USA  
Ning Zhong, Maebashi Institute of Technology, Japan     
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