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The Adaptive Web pp 54–89Cite as

User Profiles for Personalized Information Access

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Part of the Lecture Notes in Computer Science book series (LNISA,volume 4321)

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.

Keywords

  • Resource Description Framework
  • User Profile
  • Semantic Network
  • Proxy Server
  • Concept Hierarchy

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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  1. Electrical Engineering and Computer Science, Information & Telecommunication Technology Center, 2335 Irving Hill Road, Lawrence Kansas 66045-7612, USA

    Susan Gauch, Mirco Speretta & Aravind Chandramouli

  2. Department of Computer Science and Automation, Artificial Intelligence Laboratory, Roma Tre University, Via della Vasca Navale, 79 00146 Rome, Italy

    Alessandro Micarelli

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  1. Susan Gauch
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    Gauch, S., Speretta, M., Chandramouli, A., Micarelli, A. (2007). User Profiles for Personalized Information Access. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds) The Adaptive Web. Lecture Notes in Computer Science, vol 4321. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72079-9_2

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