• The ITWP workshop will be held jointly with the Workshop on Recommender Systems in E-Commerce. This will be a one-day workshop with a combined program.
• The joint program is now posted in the Workshop Program Section.

Web Personalization can be defined as any set of actions that can tailor 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. Efficient and 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 of the data, the fact that they are heterogeneous and very personal in nature, as well as the dynamic nature of user interactions with the Web. These challenges include the scalability of the personalization solutions, data integration, and successful integration of techniques from machine learning, information retrieval and filtering, databases, agent architectures, knowledge representation, data mining, text mining, statistics, information security and privacy, user modelling 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.  E-commerce and Web information systems continue to be rich sources of difficult problems and challenges for AI researchers. Web Intelligence exploits AI and advanced information technology on the Web and Internet, in order to gain business intelligence, to understand and model user behavior, and to assist users in their information seeking activities.

This workshop represents the 5th in a successful series of workshops which have been held at IJCAI and AAAI. It 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, and particularly its applications in personalization and user modelling. The goal of the workshop is to stimulate the future development of new models, methodologies, and intelligent tools for Web, including effective Web-based personalization solutions and recommender systems. 
 

User Modeling

• The use of domain knowledge and ontologies in user modeling
• User context definition and modeling
• Individual and Group user models
• Cross-Domain Models
• Privacy and Trust
• Group and community-based modeling
• Automated Techniques for user profile generation and updating
• Cognitive models for Web navigation and e-commerce interactions

• Catering to user privacy preferences
• The role of domain knowledge in preference elicitation
• Utility function elicitation from Implicit and Explicit user interaction
• Data models for Web usage, content, and structure data
• Integration of content, structure and usage data for preference discovery
• Techniques for improving online data quality
• Latent factor mining

• Personalized Search
• Scalability of personalization and recommendation techniques
• Agents for intelligent browsing and navigation
• Hybrid Recommendation System
• Conversational Recommendation Systems
• Adaptive hypertext systems
• Privacy-preserving personalization methods
• Architectures for personalized privacy

• Data/Web mining for personalization
• Link Analysis and Graph Mining
• Automated techniques for ontology generation, learning, and acquisition
• Machine Leaning techniques for information extraction and integration
• Learning metadata and Harvesting
• Web 2.0 and the Semantic Web
• Ubiquitous Environments

• User Studies
• Empirical Evaluation of systems and metrics

All submissions must be made electronically to the workshop organizers (see below).  Please use the AAAI Press prescribed formatting instructions available at http://www.aaai.org/Publications/instructions.html. Papers should be no more than 12 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. The workshop proceedings will be published and distributed by AAAI Press.

The workshop organizers also intend to edit a special issue of a journal on the workshop topics. Selected authors from the workshop will be invited to contribute to this special issue.