3rd Workshop on Computational Intelligence for Personalization in Web Content and Service Delivery (CIWP’11)

Call for Papers

  1. Scope
  2. Topics
  3. Paper Submission
  4. Organizers


Today, the explosion of multimedia content and available services prompts the need for more effective Web systems, that allow users to retrieve the right information and/or service at the right time in the right way. Personalized retrieval is a promising research direction devoted to enhance information retrieval and service customization by exploiting explicit user requests combined with implicit user preferences. User preferences are complex, heterogeneous, changing, and even contradictory. Moreover, information retrieval process is characterized by vagueness of queries and approximation in the comparison between the query content and the information in the database. Computational Intelligence (CI) provides valid tools to cope with the complexity in the mechanisms underlying Web content and service delivery personalization. Indeed, CI encloses different computing paradigms that work synergistically to exploit the tolerance for imprecision, uncertainty, approximate reasoning, and partial truth in order to provide flexible information processing capabilities and low-cost solutions. Due to these characteristics, CI techniques are suitable to deal with the imprecision and vagueness inherent a personalized information retrieval system. Recently, many researchers have addressed their interest towards the benefits of CI for personalization in Web information retrieval systems. This represents a promising direction to improve the effectiveness of such systems and to make them adaptive and more flexible.


We invite prospective authors to submit papers that propose the use of CI techniques to advance the technology in the field of Web personalization, with special focus on information retrieval and service delivery. Original contributions are solicited in the following topics (but are not limited to):

  • User behaviour modelling
  • Context-Aware Browsing
  • Automated techniques for user profiling
  • Web mining for personalization
  • Data models for Web usage, content and structure data
  • Collaborative and content based filtering
  • Clustering in personalization systems
  • Hybrid personalization systems
  • Adaptive user interfaces and personalization techniques
  • Personalized search
  • Context-aware Search
  • Service delivery personalization
  • Intelligent Context-Aware Services Delivery
  • Explanation and justification in personalization systems
  • Modelling decision making in personalization systems
  • Measuring personalization effectiveness

Paper Submission

Please follow the instructions given at the corresponding section.


visit counter