USER MODELING AND USER-ADAPTED INTERACTION
The Journal of Personalization Research 
Special Issue on
Data Mining for Personalization

Call for Papers

The continued growth and proliferation of e-commerce, online services, and Web-based information systems, has led to an explosion of available content and resources in digital form. As a result of user interactions with these resources, tremendous volumes of clickstream, transaction, and user data are collected by organizations in their daily operations. Analyzing such data can help these organizations determine the life time value of clients, design cross marketing strategies across products and services, evaluate the effectiveness of targeted promotional campaigns, and thus provide more effective personalized content to visitors. Automatic personalization is a central technology used in user-adaptive systems to deliver dynamic content, such as textual elements, links, advertisements, and product recommendations that are tailored to the needs or interests of a particular user or a segment of users.

To be able to take full advantage of the flexibility provided by such multi-channel and dynamic data, and to effectively discover user models for automatic personalization, the process of personalization can be viewed as an application of data mining requiring support for all the phases of a typical data mining cycle, including data collection, pre-processing, and integration; the application of data mining and machine learning techniques to generate useful and actionable models; the interpretation and evaluation of the discovered models; and finally the deployment of the learned knowledge to mediate between the user and the applications.

This special issue of User Modeling and User-Adapted Interaction will explore recent developments and applications of data mining and machine learning techniques in various aspects of personalization, user modeling, and user adaptive systems, including personalized or adaptive Web applications, e-commerce recommender systems, and intelligent tutoring systems.

Contributions are particularly welcome in, but not limited to, the following topics:

  • Data mining and machine learning for modeling user behavior
  • Web usage, content, and structure mining for personalized navigation
  • Automated techniques for user profile generation and updating
  • Data collection and preprocessing for user modeling and personalization
  • Integration of content, structure and usage data for personalization
  • Data modeling and visualization for user profiling
  • Modeling the evolution of user interests and preferences over time or tasks
  • Model integration for personalization and recommendation systems
  • Knowledge representation for and reasoning with user models
  • Evaluation of user models learned from data mining
  • Secure, robust, or privacy preserving techniques for personalization
  • The role of domain knowledge and ontologies in user modeling and personalization
  • Scalable collaborative filtering algorithms
  • Applications of data mining for personalized search and navigation
  • Applications of data mining in intelligent tutoring systems
  • Using text/data mining in adaptive content management and information filtering
  • Discovery and analysis of online communities and referral networks
  • Applications of data mining in business intelligence and marketing
  • Segmentation models of users and customers

How to Submit

Submissions to the special issue should follow the UMUAI formatting guidelines and submission instructions available at:  http://www.umuai.org/paper_submission.html

Each submission should note that it is intended for the Special Issue on Data Mining and Personalization.

Potential authors are asked to notify by email the guest editors as soon as possible of their intent to submit an article (see below for the relevant contact information). Sometime thereafter (but no later than a month prior to the submission deadline), they should submit a tentative title and short abstract (which can be altered for the actual submission) to assist in the formation of a panel of appropriate reviewers.

UMUAI is an archival journal that publishes mature and substantiated research results on the (dynamic) adaptation of computer systems to their human users, and the role that a model of the system about the user plays in this context. Many articles in UMUAI are quite comprehensive and describe the results of several years of work. Consequently, UMUAI gives "unlimited" space to authors (so long as what they write is important). Authors whose paper exceeds 40 pages in journal format (including illustrations and references) are however requested to supply a short justification upon submission that explains why a briefer discussion of their research results would not be advisable.

Review Process

Submissions will undergo the normal review process, and will be reviewed by three established researchers selected from a panel of reviewers formed for the special issue. Barring unforeseen problems, authors can expect to be notified regarding the review results within three months of submission.

Important Dates

Notification of Intent to Submit: as soon as possible
Submission of Title and Abstract:
January 15, 2007
Manuscript Submission:
February 15, 2007

Guest Editors

Bamshad Mobasher
mobasher@cs.depaul.edu
School of Computer Science, Telecommunication, and Information Systems
DePaul University, Chicago, USA

Alexander Tuzhilin
atuzhili@stern.nyu.edu

Stern School of Business
New York University, New York, USA