Skip to main content
SpringerLink
Log in

A Preferences Based Approach for Better Comprehension of User Information Needs

  • Chapter
  • First Online:
Book cover Transactions on Computational Collective Intelligence XVIII

Part of the book series: Lecture Notes in Computer Science ((TCCI,volume 9240))

  • 440 Accesses

Abstract

Within Mobile information retrieval research, context information provides an important basis for identifying and understanding user’s information needs. Therefore search process can take advantage of contextual information to enhance the query and adapt search results to user’s current context. However, the challenge is how to define the best contextual information to be integrated in search process. In this paper, our intention is to build a model that can identify which contextual dimensions strongly influence the outcome of the retrieval process and should therefore be in the user’s focus. In order to achieve these objectives, we create a new query language model based on user’s pereferences. We extend this model in order to define a relevance measure for each contextual dimension, which allow to automatically classify each dimension. This latter is used to compute the degree of change in result lists for the same query enhanced by different dimensions. Our experiments show that our measure can analyze the real user’s context of up to 12000 of dimensions (related to 4000 queries). We also show experimentally the quality of the set of contextual dimensions proposed, and the interest of the measure to understand mobile user’s needs and to enhance his query.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Notes

  1. 1.

    https://developers.google.com/custom-search/.

  2. 2.

    http://www.cs.waikato.ac.nz/ml/weka/.

References

  1. Abowd, G.D., Dey, A.K.: Towards a better understanding of context and context-awareness. In: Gellersen, H.-W. (ed.) HUC 1999. LNCS, vol. 1707, p. 304. Springer, Heidelberg (1999)

    Chapter  Google Scholar 

  2. Schilit, B., Adams, N., Want, R.: Context-aware computing applications. In: Proceedings of the Workshop on Mobile Computing Systems and Applications, pp. 85–90. IEEE Computer Society, Santa Cruz, CA (1994)

    Google Scholar 

  3. Kessler, C.: What is the difference? a cognitive dissimilarity measure for information retrieval result sets. J. Knowl. Inf. Syst. 30(2), 319–340 (2012)

    Article  MathSciNet  Google Scholar 

  4. Aréchiga, D., Vegas, J., Redondo, P.F.: Ontology supported personalized search for mobile devices. In: Proceedings Third International Workshop on Ontology, Conceptualization and Epistemology for Information Systems, Software Engineering and Service Science, ONTOSE. Springer LNCS, Amsterdam, pp. 1–12, 8–12 June 2009

    Google Scholar 

  5. Tsai, F.S., Etoh, M., Xie, X., Lee, W.C., Yang, Q.: Introduction to mobile information retrieval. J. IEEE Intell. Syst. 25(1), 11–15 (2010)

    Article  Google Scholar 

  6. Jelinek, F., Mercer, R.L.: Interpolated estimation of markov source parameters from sparse data. In: Proceedings of the Workshop on Pattern Recognition in Practice, pp. 381–397. North-Holland, Amsterdam, The Netherlands, May 1980

    Google Scholar 

  7. Castelli, G., Mamei, M., Rosi, A.: The whereabouts diary. In: Hightower, J., Schiele, B., Strang, T. (eds.) LoCA 2007. LNCS, vol. 4718, pp. 175–192. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  8. Ahn, J., Brusilovsky, J.P., He, D., Grady, J., Li, Q.: Personalized web exploration with task modles. In: Proceedings of WWW 2008 the 17th International Conference on World Wide Web, Beijing, China, pp. 1–10, 21–25 April 2008

    Google Scholar 

  9. Hollan, J.D., Sohn, T., Li, K.A., Griswold, W.G.: A diary study of mobile information needs. In: Proceedings of SIGCHI Conference on Human Factors in Computing Systems, pp. 433–442. ACM, Florence, Italy, 5–10 April 2008

    Google Scholar 

  10. Pitkow, J., Schutze, H., Cass, T., Cooley, R., Turnbull, D., Edmonds, A., Adar, E., Breuel, T.: Personalized search. Commun. ACM J. 45(9), 50–55 (2002)

    Google Scholar 

  11. Ponte, J.M., Croft, W.B.: A language modeling approach to information retrieval. In: Proceedings of the 21st International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 275–281. ACM, Melbourne, Australia, August 1998

    Google Scholar 

  12. Stefanidis, K., Pitoura, E., Vassiliadis, P.: Adding context to preferences. In: Proceedings of ICDE IEEE 23rd International Conference on Data Engineering, Istanbul, Turkey, pp. 846–855, 15–20 April 2007

    Google Scholar 

  13. Gravano, L., Hatzivassiloglou, V., Lichtenstein, R.: Categorizing web queries according to geographical locality. In: Proceedings of CIKM 2003 the Twelfth International Conference on Information and Knowledge Management, pp. 325–333. ACM, New Orleans, Louisiana, USA, 2–8 November 2003

    Google Scholar 

  14. Arias, M., Cantera, de la Fuente, P., Llamas, C., Vegas, J.: Knowledge-based thesaurus recommender system in mobile web search, In: Proceedings of CERI 1st Spanish Conference on Information Retrieval, Madrid, Spain, 15–16 June 2010

    Google Scholar 

  15. Welch, M., Cho, J.: Automatically identifying localizable queries. In: Proceedings of 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1185–1186. ACM, Singapore, 20–24 July 2008

    Google Scholar 

  16. Kamvar, M., Baluja, S.: A large scale study of wireless search behavior : Google mobile search. In: Proceedings of the SIGCHI 2006 the SIGCHI Conference on Human Factors in Computing Systems, pp. 701–709. ACM, Montreal, Quebec, Canada, 22–27 April 2006

    Google Scholar 

  17. Matsuda, N., Hirashima, T., Nomoto, T., Taki, H., Toyoda, J.I.: Context-sensitive filtering for the Web. J. Web Intell. Agent Syst. 1(3), 249–257

    Google Scholar 

  18. Bouidghaghen, O., Tamine, L., Boughanem, M.: Context-aware user’s interests for personalizing mobile search. In: Proceedings 12th IEEE International Conference on Mobile Data Management, pp. 129–134. IEEE Computer Society, Sweden, 6–9 June 2011

    Google Scholar 

  19. Chirita, P., Firan, C., Nejdl, W.: Summarizing local context to personalize global web search. In: Proceedings of CIKM International Conference on Information and Knowledge Management, pp. 287–296. ACM, Arlington, Virginia, USA, 6–11 November 2006

    Google Scholar 

  20. Coppola, P., Della Mea, V., Di Gaspero, L., Menegon, D., Mischis, D., Mizzaro, S., Scagnetto, I., Vassena, L.: The context-aware browser. J. IEEE Intell. Syst. 25(1), 38–47 (2010)

    Article  Google Scholar 

  21. Ingwersen, P., Jarvelin, K.: The Turn: Integration of Information Seeking and Retrieval in Context, vol. 18, p. 448. Springer, New York (2005)

    Google Scholar 

  22. Roman, P.E., Dell, R.F., Velasquez, J.D., Heufeman, P.L.: Identifying user sessions from web server logs with integer programming. J. Intell. Data Anal. 18(1), 43–61

    Google Scholar 

  23. McParlane, P.J., Moshfeghi, Y., Jose, J.M.: On contextual photo tag recommendation. In: Proceedings of SIGIR 2013 the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 965–968. ACM, Dublin, Ireland, 28 July –01 August 2013

    Google Scholar 

  24. Jones, R.: Temporal profiles of queries. J. ACM Trans. Inf. Syst. TOIS 25(3), 14 (2007)

    Article  Google Scholar 

  25. De Virgilio, R., Torlone, R.: Modeling heterogeneous context information in adaptive web based applications. In: Proceedings of ICWE 6th International Conference on Web Engineering, pp. 56–63. ACM, Palo Alto, California, USA, 11–14 July 2006

    Google Scholar 

  26. Cronen-Townsend, S., Zhou, Y., Croft, W.B.: Predicting query performance. In: Proceedings the 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 299–306. ACM, Tampere, Finland, 11–15 August 2002

    Google Scholar 

  27. Eguchi, S., Copas, J.: Interpreting Kullback Leibler divergence with the Neyman-Pearson lemma. J. Multivariate Anal. 97, 2034–2040 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  28. Missaoui, S., Faiz, R.: A new preference based model for relevant dimension identification in contextual mobile search. In: Noubir, G., Raynal, M. (eds.) Networked Systems. LNCS, vol. 8593, pp. 215–229. Springer, Heidelberg (2014)

    Google Scholar 

  29. Poslad, S., Laamanen, H., Malaka, R., Nick, A., Buckle, P., Zipf, A.: Crumpet, Creation of user-friendly mobile services personalised for tourism. In: Proceedings of the Second International Conference on 3G Mobile Communication Technologies, Conference Publication No. 477, pp. 28–32. IEEE Computer Society, London, 26–28 March 2001

    Google Scholar 

  30. Vadrevu, S., Zhang, Y., Tseng, B., Sun, G., Li, X.: Identifying regional sensitive queries in web search. In: Proceedings of WWW 2008 the 17th International Conference on World Wide Web, pp. 1185–1186, Beijing, China, 21–25 April 2008

    Google Scholar 

  31. Yau, S., Liu, H., Huang, D., Yao, Y.: Situation-aware personalized Information retrieval for mobile internet. In: Proceedings of COMPSAC 27th Annual International Computer Software and Applications Conference, pp. 639–644. IEEE Computer Society, Dallas, TX, USA, 3–6 November 2003

    Google Scholar 

  32. Gross, T., Klemke, R.: Context modelling for information retrieval: requirements and approaches. IADIS Int. J. WWW/Internet 6(1), 29–42 (2003)

    Google Scholar 

  33. Lavrenko, V., Croft, W.B.: Relevance-based language models. In: Proceedings of SIGIR 2001 the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 120–127. ACM, New Orleans, Louisiana, USA, 9–13 September 2001

    Google Scholar 

  34. Varma, V., Sriharsha, N., Pingali, P.: Personalized web search engine for mobile devices. In: Proceedings of IIIA International Workshop on Intelligent Information Access, Marina Congress Center, Helsinki, Finland, 6–8 July 2006

    Google Scholar 

  35. Croft, W.B., Lafferty, J. (eds.): Language Modeling for Information Retrieval. Kluwer Academic Publishers, Dordrecht (2003)

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. LARODEC, ISG, University of Tunis, Bardo, Tunisia

    Sondess Missaoui

  2. LARODEC, IHEC Carthage University, Carthage Presidency, Carthage, Tunisia

    Rim Faiz

Authors
  1. Sondess Missaoui
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rim Faiz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sondess Missaoui .

Editor information

Editors and Affiliations

  1. Wroclaw University of Technology, Department of Information Systems, Wroclaw, Poland

    Ngoc Thanh Nguyen

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Missaoui, S., Faiz, R. (2015). A Preferences Based Approach for Better Comprehension of User Information Needs. In: Nguyen, N. (eds) Transactions on Computational Collective Intelligence XVIII. Lecture Notes in Computer Science(), vol 9240. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48145-5_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-48145-5_4

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-48144-8

  • Online ISBN: 978-3-662-48145-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation