User profiles for personalized information access

  • Authors:

  • Susan Gauch;Mirco Speretta;Aravind Chandramouli;Alessandro Micarelli

  • Affiliations:

  • Electrical Engineering and Computer Science, Information & Telecommunication Technology Center, Lawrence, Kansas;Electrical Engineering and Computer Science, Information & Telecommunication Technology Center, Lawrence, Kansas;Electrical Engineering and Computer Science, Information & Telecommunication Technology Center, Lawrence, Kansas;Department of Computer Science and Automation, Artificial Intelligence Laboratory, Roma Tre University, Rome, Italy

  • Venue:
  • The adaptive web
  • Year:
  • 2007

Quantified Score

Hi-index 0.00

Visualization

Abstract

The amount of information available online is increasing exponentially. While this information is a valuable resource, its sheer volume limits its value. Many research projects and companies are exploring the use of personalized applications that manage this deluge by tailoring the information presented to individual users. These applications all need to gather, and exploit, some information about individuals in order to be effective. This area is broadly called user profiling. This chapter surveys some of the most popular techniques for collecting information about users, representing, and building user profiles. In particular, explicit information techniques are contrasted with implicitly collected user information using browser caches, proxy servers, browser agents, desktop agents, and search logs. We discuss in detail user profiles represented as weighted keywords, semantic networks, and weighted concepts. We review how each of these profiles is constructed and give examples of projects that employ each of these techniques. Finally, a brief discussion of the importance of privacy protection in profiling is presented.