Skip to main content
Springer Nature Link
Log in

A Social Semantic Approach to Adaptive Query Expansion

  • Conference paper
  • First Online:
Web Information Systems and Technologies (WEBIST 2014)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 226))

Included in the following conference series:

  • 677 Accesses

Abstract

Classic query expansion approaches are based on the use of two-dimensional co-occurrence matrices. In this paper, we propose the adoption of three-dimensional matrices, where the added dimension is represented by semantic classes (i.e., categories comprising all the terms that share a semantic property) related to the folksonomy extracted from social bookmarking services, such as Delicious and StumbleUpon. The results of an in-depth experimental evaluation performed on real users show that our approach outperforms traditional techniques, so confirming the validity and usefulness of the categorization of the user needs and preferences in semantic classes.

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

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    delicious.com.

  2. 2.

    stumbleupon.com.

  3. 3.

    wordnet.princeton.edu.

  4. 4.

    www.ontologyportal.org.

References

  1. Abouenour, L., Bouzouba, K., Rosso, P.: An evaluated semantic query expansion and structure-based approach for enhancing arabic question answering. Int. J. Inf. Commun. Technol. 3(3), 37–51 (2010)

    Google Scholar 

  2. Baeza-Yates, R.A., Ribeiro-Neto, B.A.: Modern Information Retrieval. ACM Press / Addison-Wesley, Boston, MA, USA (1999)

    Google Scholar 

  3. Bai, J., Song, D., Bruza P., Nie, J.Y., Cao, G.: Query expansion using term relationships in language models for information retrieval. In: Proceedings of the 14th ACM International Conference on Information and Knowledge Management, pp. 688–695 (2005)

    Google Scholar 

  4. Biancalana, C., Flamini, A., Gasparetti, F., Micarelli, A., Millevolte, S., Sansonetti, G.: Enhancing traditional local search recommendations with context-awareness. In: Konstan, J.A., Conejo, R., Marzo, J.L., Oliver, N. (eds.) UMAP 2011. LNCS, vol. 6787, pp. 335–340. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  5. Biancalana, C., Gasparetti, F., Micarelli, A., Sansonetti, G.: Enhancing query expansion through folksonomies and semantic classes. In: 2012 International Conference on Privacy, Security, Risk and Trust (PASSAT), International Conference on Social Computing (SocialCom), pp. 611–616, September 2012

    Google Scholar 

  6. Biancalana, C., Gasparetti, F., Micarelli, A., Sansonetti, G.: An approach to social recommendation for context-aware mobile services. ACM Trans. Intell. Syst. Technol. 4(1), 10:1–10:31 (2013)

    Article  Google Scholar 

  7. Biancalana, C., Gasparetti, F., Micarelli, A., Sansonetti, G.: Social semantic query expansion. ACM Trans. Intell. Syst. Technol. 4(4), 60:1–60:43 (2013)

    Article  Google Scholar 

  8. Biancalana, C., Lapolla, A., Micarelli, A.: Personalized web search using correlation matrix for query expansion. In: Cordeiro, J., Hammoudi, S., Filipe, J. (eds.) Web Information Systems and Technologies. LNBIP, vol. 18, pp. 186–198. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  9. Biancalana, C., Micarelli, A.: Social tagging in query expansion: a new way for personalized web search. In: CSE (4), pp. 1060–1065 (2009)

    Google Scholar 

  10. Bilotti, M.W., Katz, B., Lin, J.: What works better for question answering: stemming or morphological query expansion? In: Proceedings of the Information Retrieval for Question Answering (IR4QA) Workshop at SIGIR 2004, Sheffield (2004)

    Google Scholar 

  11. Burgess, C., Lund, K.: Hyperspace analog to language (hal): a general model of semantic representation. In: Proceedings of the Annual Neeting of the Psychonomic Society (1995)

    Google Scholar 

  12. Cao, G., Nie, J.-Y., Gao, J., Robertson, S.:Selecting good expansion terms for pseudo-relevance feedback. In: Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2008, pp. 243–250, New York (2008)

    Google Scholar 

  13. Carman, M.J., Baillie, M., Gwadera, R., Crestani, F.: A statistical comparison of tag and query logs. In: Proceedings of the 32nd International ACM SIGIR Conference onResearch and Development in Information Retrieval, SIGIR 2009, pp. 123–130, New York (2009)

    Google Scholar 

  14. Carpineto, C., Romano, G.: A survey of automatic query expansion in information retrieval. ACM Comput. Surv. 44(1), 1:1–1:50 (2012)

    Article  MATH  Google Scholar 

  15. Cui, H., Wen, J.-R., Nie, J.-Y., Ma, W.-Y.: Query expansion by mining user logs. IEEE Trans. Knowl. Data Eng. 15(4), 829–839 (2003)

    Article  Google Scholar 

  16. Micarelli, A.G.F., Sansonetti, G.: Exploiting web browsing activities for user needs identification. In: Proceedings of the 2014 International Conference on Computational Science and Computational Intelligence (CSCI 2014), IEEE Computer Society, Conference Publishing Services, March 2014

    Google Scholar 

  17. Jansen, B.J., Spink, A., Pedersen, J.: A temporal comparison of altavista web searching: research articles. J. Am. Soc. Inf. Sci. Technol. 56(6), 559–570 (2005)

    Article  Google Scholar 

  18. Jansen, B.J., Spink, A., Saracevic, T.: Real life, real users, and real needs: a study and analysis of user queries on the web. Inf. Process. Manage. 36(2), 207–227 (2000)

    Article  Google Scholar 

  19. Järvelin, K., Kekäläinen, J.: IR evaluation methods for retrieving highly relevant documents. In: Proceedings of the 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, New York, USA, pp. 41–48, (2000)

    Google Scholar 

  20. Järvelin, K., Kekäläinen, J.: Cumulated gain-based evaluation of IR techniques. ACM Trans. Inf. Syst. 20(4), 422–446 (2002)

    Article  Google Scholar 

  21. Kim, M.-C., Choi, K.-S.: A comparison of collocation-based similarity measures in query expansion. Inf. Process. Manage. 35(1), 19–30 (1999)

    Article  Google Scholar 

  22. Nanba, H.: Query expansion using an automatically constructed thesaurus. In: Kando, N., Evans, D.K. (eds) Proceedings of the Sixth NTCIR Workshop Meeting on Evaluation of Information Access Technologies: Information Retrieval, Question Answering, and Cross-Lingual Information Access, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101–8430, Japan, pp. 414–419, May 2007

    Google Scholar 

  23. Niles, I., Pease, A.: Linking lexicons and ontologies: mapping wordnet to the suggested upper merged ontology. In: Proceedings of the IEEE International Conference on Information and Knowledge Engineering, Las Vegas, Nevada, USA, pp. 412–416, (2003)

    Google Scholar 

  24. Peat, H.J., Willett, P.: The limitations of term co-occurrence data for query expansion in document retrieval systems. J. American Soc. Inf. Sci. 42, 378–383 (1991)

    Article  Google Scholar 

  25. Xu, Y., Jones, G.J.F., Wang, B.: Query dependent pseudo-relevance feedback based on wikipedia. In: Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009, pp. 59–66, New York (2009)

    Google Scholar 

  26. Eli Zamir, O., Korn, J.L., Fikes, A.B., Lawrence, S.R.: Us patent application #0050240580: Personalization of placed content ordering in search results, July 2004

    Google Scholar 

  27. Zhou, D., Lawless, S., Wade, V.: Improving search via personalized query expansion using social media. Inf. Retr. 15(3–4), 218–242 (2012)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Engineering, Artificial Intelligence Laboratory, Roma Tre University, Via della Vasca Navale, 79, 00146, Rome, Italy

    Claudio Biancalana, Fabio Gasparetti, Alessandro Micarelli & Giuseppe Sansonetti

Authors
  1. Claudio Biancalana
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Fabio Gasparetti
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Alessandro Micarelli
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Giuseppe Sansonetti
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Giuseppe Sansonetti .

Editor information

Editors and Affiliations

  1. University of Paris, Paris, Paris, France

    Valérie Monfort

  2. RWTH Aachen University, Aachen, Germany

    Karl-Heinz Krempels

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Biancalana, C., Gasparetti, F., Micarelli, A., Sansonetti, G. (2015). A Social Semantic Approach to Adaptive Query Expansion. In: Monfort, V., Krempels, KH. (eds) Web Information Systems and Technologies. WEBIST 2014. Lecture Notes in Business Information Processing, vol 226. Springer, Cham. https://doi.org/10.1007/978-3-319-27030-2_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-27030-2_8

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27029-6

  • Online ISBN: 978-3-319-27030-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics