Skip to main content

Detecting Session Boundaries to Personalize Search Using a Conceptual User Context

  • Chapter
Book cover Advances in Electrical Engineering and Computational Science

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 39))

Most popular Web search engines are carachterized by “one size fits all” approaches. Involved retrieval models are based on the query-document matching without considering the user context, interests ang goals during the search. Personalized Web search tackles this problem by considering the user interests in the search process. In this chapter, we present a personalized search approach which adresses two key challenges. The first one is to model a conceptual user context across related queries using a session boundary detection. The second one is to personalize the search results using the user context. Our experimental evaluation was carried out using the TREC collection and shows that our approach is effective.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bin Tan, Xuehua Shen, and ChengXiang Zhai. Mining long-term search history to improve search accuracy. In KDD '06: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 718–723, New York, NY, USA, 2006. ACM.

    Google Scholar 

  2. Smitha Sriram, Xuehua Shen, and Chengxiang Zhai. A session-based search engine. In SIGIR'04: Proceedings of the International ACM SIGIR Conference, 2004.

    Google Scholar 

  3. Fang Liu, Clement Yu, and Weiyi Meng. Personalized web search for improving retrieval effectiveness. IEEE Transactions on Knowledge and Data Engineering, 16(1):28–40, 2004.

    Article  Google Scholar 

  4. Ahu Sieg, Bamshad Mobasher, and Robin Burke. Web search personalization with ontological user profiles. In Proceedings of the CIKM'07 conference, pages 525–534, New York, NY, USA, 2007. ACM.

    Google Scholar 

  5. Lynda Tamine-Lechani, Mohand Boughanem, Nesrine Zemirli. Personalized document ranking: exploiting evidence from multiple user interests for profiling and retrieval. to appear. In Journal of Digital Information Management, vol. 6, issue 5, 2008, pp. 354–366.

    Google Scholar 

  6. John Paul Mc Gowan. A multiple model approach to personalised information access. Master thesis in computer science, Faculty of science, Universit de College Dublin, February 2003.

    Google Scholar 

  7. Alessandro Micarelli and Filippo Sciarrone. Anatomy and empirical evaluation of an adaptive web-based information filtering system. User Modeling and User-Adapted Interaction, 14(2– 3):159–200, 2004.

    Google Scholar 

  8. Hyoung R. Kim and Philip K. Chan. Learning implicit user interest hierarchy for context in personalization. In Proceedings of IUI '03, pages 101–108, New York, NY, USA, 2003. ACM.

    Google Scholar 

  9. Susan Gauch, Jason Chaffee, and Alaxander Pretschner. Ontology-based personalized search and browsing. Web Intelli. and Agent Sys., 1(3–4):219–234, 2003.

    Google Scholar 

  10. Ahu Sieg, Bamshad Mobasher, Steve Lytinen, Robin Burke. Using concept hierarchies to enhance user queries in web-based information retrieval. In The IASTED International Conference on Artificial Intelligence and Applications. Innsbruck, Austria, 2004.

    Google Scholar 

  11. Mariam Daoud, Lynda Tamine-Lechani, and Mohand Boughanem. Using a concept-based user context for search personalization. to appear. In Proceedings of the 2008 International Conference of Data Mining and Knowledge Engineering (ICDMKE'08), pages 293–298. IAENG, 2008.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer Science+Business Media B.V

About this chapter

Cite this chapter

Daoud, M., Boughanem, M., Tamine-Lechani, L. (2009). Detecting Session Boundaries to Personalize Search Using a Conceptual User Context. In: Ao, SI., Gelman, L. (eds) Advances in Electrical Engineering and Computational Science. Lecture Notes in Electrical Engineering, vol 39. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-2311-7_40

Download citation

  • DOI: https://doi.org/10.1007/978-90-481-2311-7_40

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-2310-0

  • Online ISBN: 978-90-481-2311-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics