Skip to main content

Determining the Optimal Session Interval for Transaction Log Analysis of an Online Library Catalogue

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9626))

Abstract

Transaction log analysis at the level of a session is commonly used as a means of understanding user-system interactions. A key practical issue in the process of conducting session level analysis is the segmentation of the logs into appropriate user sessions (i.e., sessionisation). Methods based on time intervals are frequently used as a simple and convenient means of carrying out this segmentation task. However, little work has been carried out to determine whether the commonly applied 30-minute period is appropriate, particularly for the analysis of search logs from library catalogues. Comparison of a range session intervals with human judgements demonstrate that the overall accuracy of session segmentation is relatively constant for session intervals between 26 to 57 min. However, a session interval of between 25 and 30 min minimises the chances of one error type (incorrect collation or incorrect segmentation) predominating.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
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

Learn about institutional subscriptions

References

  1. Catledge, L.D., Pitkow, J.E.: Characterizing browsing strategies in the World-Wide Web. Comput. Netw. Isdn. 27(6), 1065–1073 (1995)

    Article  Google Scholar 

  2. Cooper, M.D.: Usage patterns of a web-based library catalog. J. Am. Soc. Inf. Sci. Tec. 52(2), 137–148 (2001)

    Article  Google Scholar 

  3. Dogan, R.I., Murray, G.C., Névéol, A., Lu, Z.: Understanding PubMed® user search behavior through log analysis. Database 2009 (bap018) (2009)

    Google Scholar 

  4. Gayo-Avello, D.: A survey on session detection methods in query logs and a proposal for future evaluation. Inf. Sci. 179(12), 1822–1843 (2009)

    Article  Google Scholar 

  5. Göker, A., He, D.: Analysing web search logs to determine session boundaries for user-oriented learning. In: Brusilovsky, P., Stock, O., Strapparava, C. (eds.) AH 2000. LNCS, vol. 1892, p. 319. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  6. Goodale, P., Clough, P.: Report on Evaluation of the Search25 Demo System. University of Sheffield, Sheffield (2012)

    Google Scholar 

  7. Han, H., Jeong, W., Wolfram, D.: Log analysis of academic digital library: User query patterns. In: 10th iConference, pp. 1002–1008. Ideals, Illinois (2014)

    Google Scholar 

  8. Jansen, B.: Search log analysis: What it is, what’s been done, how to do it. Libr. Inform. Sci. Res. 28(3), 407–432 (2006)

    Article  Google Scholar 

  9. Jansen, B.J., Spink, A., Kathuria, V.: How to define searching sessions on web search engines. In: Nasraoui, O., Spiliopoulou, M., Srivastava, J., Mobasher, B., Masand, B. (eds.) WebKDD 2006. LNCS (LNAI), vol. 4811, pp. 92–109. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  10. Jones, R., Klinkner, K.L.: Beyond the session timeout: automatic hierarchical segmentation of search topics in query logs. In: 17th ACM conference on Information and knowledge management, pp. 699–708. ACM, New York (2008)

    Google Scholar 

  11. Jones, S., Cunningham, S.J., McNab, R., Boddie, S.: A transaction log analysis of a digital library. Int. J. Digit. Libr. 3(2), 152–169 (2000)

    Article  Google Scholar 

  12. Kapusta, J., Munk, M., Drlík, M.: Cut-off time calculation for user session identification by reference length. In: 6th International Conference on Application of Information and Communication Technologies (AICT), pp. 1–6. IEEE, New York (2012)

    Google Scholar 

  13. Lown, C.: A transaction log analysis of NCSU’s faceted navigation OPAC. School of Information and Library Science, University of North Carolina (2008)

    Google Scholar 

  14. Malliari, A., Kyriaki-Manessi, D.: Users’ behaviour patterns in academic libraries’ OPACs: a multivariate statistical analysis. New Libr. World 108(3/4), 107–122 (2007)

    Article  Google Scholar 

  15. Meadow, K., Meadow, J.: Search query quality and web-scale discovery: A qualitative and quantitative analysis. College Undergraduate Librar. 19(2–4), 163–175 (2012)

    Article  Google Scholar 

  16. Montgomery, A., Faloutsos, C.: Identifying web browsing trends and patterns. IEEE Comput. 34(7), 94–95 (2007)

    Article  Google Scholar 

  17. Nicholas, D., Huntington, P., Jamali, H.R.: User diversity: as demonstrated by deep log analysis. Electron. Libr. 26(1), 21–38 (2008)

    Article  Google Scholar 

  18. Niu, X., Zhang, T., Chen, H.L.: Study of user search activities with two discovery tools at an academic library. Int. J. Hum. Comput. Interact. 30(5), 422–433 (2014)

    Article  Google Scholar 

  19. Peters, T.A.: The history and development of transaction log analysis. Libr. Hi Tech. 11(2), 41–66 (1993)

    Article  Google Scholar 

  20. Spink, A., Park, M., Jansen, B.J., Pedersen, J.: Multitasking during web search sessions. Inform. Process. Manag. 42(1), 264–275 (2006)

    Article  Google Scholar 

  21. Yardley, L.: Demonstrating validity in qualitative psychology. In: Smith, J.A. (ed.) Qualitative psychology: A practical guide to research methods, pp. 235–251. SAGE, London, UK (2008)

    Google Scholar 

  22. Ye, C., Wilson, M.L.: A user defined taxonomy of factors that divide online information retrieval sessions. In: 5th Information Interaction in Context Symposium, pp. 48–57. ACM, New York (2014)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Simon Wakeling .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Wakeling, S., Clough, P. (2016). Determining the Optimal Session Interval for Transaction Log Analysis of an Online Library Catalogue. In: Ferro, N., et al. Advances in Information Retrieval. ECIR 2016. Lecture Notes in Computer Science(), vol 9626. Springer, Cham. https://doi.org/10.1007/978-3-319-30671-1_56

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-30671-1_56

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-30670-4

  • Online ISBN: 978-3-319-30671-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics