Self-tuning Personalized Information Retrieval in an Ontology-Based Framework

Castells, Pablo; Fernandez, Miriam; Vallet, David; Mylonas, Phivos and Avrithis, Yannis (2005). Self-tuning Personalized Information Retrieval in an Ontology-Based Framework. In: On the Move to Meaningful Internet Systems 2005: OTM 2005 Workshops, pp. 977–986.

DOI: https://doi.org/10.1007/11575863_119

Abstract

Reliability is a well-known concern in the field of personalization technologies. We propose the extension of an ontology-based retrieval system with semantic-based personalization techniques, upon which automatic mechanisms are devised that dynamically gauge the degree of personalization, so as to benefit from adaptivity but yet reduce the risk of obtrusiveness and loss of user control. On the basis of a common domain ontology KB, the personalization framework represents, captures and exploits user preferences to bias search results towards personal user interests. Upon this, the intensity of personalization is automatically increased or decreased according to an assessment of the imprecision contained in user requests and system responses before personalization is applied.

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About

• Item ORO ID
• 28603
• Item Type
• Conference or Workshop Item
• ISSN
• 1611-3349
• Project Funding Details

• Funded Project Name	Project ID	Funding Body
  Not Set	Not Set	European Commission under contract FP6- 001765 aceMedia

• Extra Information
• ISBN: 978-3-540-29739-0
  Series: LNCS Vol 3762 p. 977-986
  
  The original publication is available at www.springerlink.com
• Academic Unit or School
• Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
  Faculty of Science, Technology, Engineering and Mathematics (STEM)
• Research Group
• Centre for Research in Computing (CRC)
• Copyright Holders
• © 2005 Springer Verlag
• Depositing User
• Kay Dave