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Article

How to define searching sessions on web search engines

Published: 20 August 2006 Publication History

Abstract

In this research, we investigate three techniques for defining user sessions on Web search engines. We analyze 2,465,145 interactions from 534,507 Web searchers. We compare three methods for defining sessions using: 1) Internet Protocol address and cookie; 2) Internet Protocol address, cookie, and a temporal limit on intra-session interactions; and 3) Internet Protocol address, cookie, and query reformulation patterns. Research results shows that defining sessions by query reformulation provides the best measure of session identification, with a nearly 95% accuracy. This method also results in an 82% increase in the number of sessions compared to Internet Protocol address and cookie alone. Regardless of the method, mean session length was fewer than three queries and the mean session duration was less than 30 minutes. Implications are that unique sessions may be a better indicator than the common industry metric of unique visitors for measuring search traffic. Results of this research may lead to tools to better support Web searching.

References

[1]
Anick, P.: Using Terminological Feedback for Web Search Refinement - a Log-Based Study. In: Twenty-Sixth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Toronto, Canada, pp. 88-95. ACM, New York (2003).
[2]
Beitzel, S.M., Jensen, E.C., Chowdhury, A., Grossman, D., Frieder, O.: Hourly Analysis of a Very Large Topically Categorized Web Query Log. In: 27th annual international conference on Research and development in information retrieval, Sheffield, U.K., pp. 321-328 (2004).
[3]
Belkin, N., Cool, C., Kelly, D., Lee, H.-J., Muresan, G., Tang, M.-C., Yuan, X.-J.: Query Length in Interactive Information Retrieval. In: 26th Annual international ACM Conference on Research and Development in Information Retrieval, Toronto, Canada, pp. 205-212. ACM Press, New York (2003).
[4]
Belkin, N., Oddy, R., Brooks, H.: Ask for Information Retrieval, Parts 1 & 2. Journal of Documentation 38, 61-7, 145-164 (1982).
[5]
Bodoff, D.: Relevance for Browsing, Relevance for Searching. Journal of the American Society of Information Science and Technology 57, 69-86 (2006).
[6]
Catledge, L.D., Pitkow, J.E.: Characterizing Browsing Strategies in the World Wide Web. Computer Network and ISDN Systems 27, 1065-1073 (1995).
[7]
Hansen, M.H., Shriver, E.: Using Navigation Data to Improve Ir Functions in the Context of Web Search. In: Tenth International Conference on Information and Knowledge Management, Atlanta, Georgia, USA, pp. 135-142 (2001).
[8]
He, D., Göker, A., Harper, D.J.: Combining Evidence for Automatic Web Session Identification. Information Processing & Management 38, 727-742 (2002).
[9]
Jansen, B.J.: Seeking and Implementing Automated Assistance During the Search Process. Information Processing & Management 41, 909-928 (2005).
[10]
Jansen, B.J.: Using Temporal Patterns of Interactions to Design Effective Automated Searching Assistance Systems. Communications of the ACM 49, 72-74 (2006).
[11]
Jansen, B.J., McNeese, M.D.: Evaluating the Effectiveness of and Patterns of Interactions with Automated Searching Assistance. Journal of the American Society for Information Science and Technology 56, 1480-1503 (2005).
[12]
Jansen, B.J., Pooch, U.: Web User Studies: A Review and Framework for Future Work. Journal of the American Society of Information Science and Technology 52, 235-246 (2001).
[13]
Jansen, B.J., Spink, A.: An Analysis of Web Information Seeking and Use: Documents Retrieved Versus Documents Viewed. In: 4th International Conference on Internet Computing, Las Vegas, Nevada, pp. 65-69 (2003).
[14]
Jansen, B.J., Spink, A.: An Analysis of Web Searching by European Alltheweb. Information Processing & Management 41, 361-381 (2005).
[15]
Jansen, B.J., Spink, A.: How Are We Searching the World Wide Web? A Comparison of Nine Search Engine Transaction Logs. Information Processing & Management 42, 248- 263 (2005).
[16]
Jansen, B.J., Spink, A., Blakely, C., Koshman, S.: Web Searcher Interaction with the Dogpile.Com Meta-Search Engine. Journal of the American Society for Information Science and Technology (forthcoming).
[17]
Jansen, B.J., Spink, A., Pedersen, J.: Trend Analysis of Altavista Web Searching. Journal of the American Society for Information Science and Technology 56, 559-570 (2005).
[18]
Koshman, S., Spink, A., Jansen, B.J., Park, M., Field, C.: Web Searching on the Vivisimo Search Engine. Journal of the American Society of Information Science and Technology (forthcoming).
[19]
Lau, T., Horvitz, E.: Patterns of Search: Analyzing and Modeling Web Query Refinement. In: 7th International Conference on User Modeling, Banff, Canada, pp. 119- 128 (1999).
[20]
Lawrence, S., Giles, C.L., Bollacker, K.: Digital Libraries and Autonomous Citation Indexing. IEEE Computer 32, 67-71 (1999).
[21]
Montgomery, A., Faloutsos, C.: Trends and Patterns of Www Browsing Behaviour. In: Ziarko, W., Yao, Y. (eds.) RSCTC 2000. LNCS (LNAI), vol. 2005, Springer, Heidelberg (2001).
[22]
Montgomery, A., Faloutsos, C.: Identifying Web Browsing Trends and Patterns. IEEE Computer 34, 94-95 (2001).
[23]
Özmutlu, H.C., Cavdur, F.: Application of Automatic Topic Identification on Excite Web Search Engine Data Logs. Information Processing & Management 41, 1243-1262 (2005).
[24]
Özmutlu, H.C., Çavdur, F., Spink, A., Özmutlu, S.: Cross Validation of Neural Network Applications for Automatic New Topic Identification. In: ASIST 2005. Association for the American Society of Information Science and Technology, Charlotte, NC, pp. 1-10 (2005).
[25]
Park, S., Bae, H., Lee, J.: End User Searching: A Web Log Analysis of Naver, a Korean Web Search Engine. Library & Information Science Research 27, 203-221 (2005).
[26]
Radlinski, F., Joachims, T.: Query Chains: Learning to Rank from Implicit Feedback. In: KDD 2005. Eleventh ACM SIGKDD international conference on Knowledge discovery in data mining, Chicago, Illinois, pp. 239-248 (2005).
[27]
Shneiderman, B., Byrd, D., Croft, W.B.: Sorting out Searching: A User-Interface Framework for Text Searches. Communications of the ACM 41, 95-98 (1998).
[28]
Silverstein, C., Henzinger, M., Marais, H., Moricz, M.: Analysis of a Very Large Web Search Engine Query Log. SIGIR Forum 33, 6-12 (1999).
[29]
Spink, A., Jansen, B.J.: Web Search: Public Searching of the Web. Kluwer, New York (2004).
[30]
Spink, A., Jansen, B.J., Blakely, C., Koshman, S.: A Study of Results Overlap and Uniqueness among Major Web Search Engines. In: Information Processing & Management (forthcoming).
[31]
Spink, A., Jansen, B.J., Wolfram, D., Saracevic, T.: From E-Sex to E-Commerce: Web Search Changes. IEEE Computer 35, 107-111 (2002).
[32]
Spink, A., Özmutlu, H.C., Özmutlu, S.: Multitasking Information Seeking and Searching Processes. Journal of the American Society for Information Science and Technology 53, 639-652 (2002).
[33]
Spink, A., Park, M., Jansen, B.J., Pedersen, J.: Multitasking During Web Search Sessions. Information Processing & Management 42, 264-275 (2005).

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  • (2023)Bibliometric‐enhanced legal information retrievalJournal of the Association for Information Science and Technology10.1002/asi.2479974:8(1010-1025)Online publication date: 1-Jul-2023
  • (2018)Consistent Transformation of Ratio Metrics for Efficient Online Controlled ExperimentsProceedings of the Eleventh ACM International Conference on Web Search and Data Mining10.1145/3159652.3159699(55-63)Online publication date: 2-Feb-2018
  • (2017)Using the Delay in a Treatment Effect to Improve Sensitivity and Preserve Directionality of Engagement Metrics in A/B ExperimentsProceedings of the 26th International Conference on World Wide Web10.1145/3038912.3052664(1301-1310)Online publication date: 3-Apr-2017
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Published In

cover image Guide Proceedings
WebKDD'06: Proceedings of the 8th Knowledge discovery on the web international conference on Advances in web mining and web usage analysis
August 2006
247 pages
ISBN:354077484X

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 20 August 2006

Author Tags

  1. Markov states
  2. query reformulation
  3. web queries
  4. web sessions

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Cited By

View all
  • (2023)Bibliometric‐enhanced legal information retrievalJournal of the Association for Information Science and Technology10.1002/asi.2479974:8(1010-1025)Online publication date: 1-Jul-2023
  • (2018)Consistent Transformation of Ratio Metrics for Efficient Online Controlled ExperimentsProceedings of the Eleventh ACM International Conference on Web Search and Data Mining10.1145/3159652.3159699(55-63)Online publication date: 2-Feb-2018
  • (2017)Using the Delay in a Treatment Effect to Improve Sensitivity and Preserve Directionality of Engagement Metrics in A/B ExperimentsProceedings of the 26th International Conference on World Wide Web10.1145/3038912.3052664(1301-1310)Online publication date: 3-Apr-2017
  • (2015)Practical Aspects of Sensitivity in Online Experimentation with User Engagement MetricsProceedings of the 24th ACM International on Conference on Information and Knowledge Management10.1145/2806416.2806496(763-772)Online publication date: 17-Oct-2015
  • (2015)Future User Engagement Prediction and Its Application to Improve the Sensitivity of Online ExperimentsProceedings of the 24th International Conference on World Wide Web10.1145/2736277.2741116(256-266)Online publication date: 18-May-2015
  • (2015)Engagement Periodicity in Search Engine UsageProceedings of the Eighth ACM International Conference on Web Search and Data Mining10.1145/2684822.2685318(27-36)Online publication date: 2-Feb-2015
  • (2013)Online multitasking and user engagementProceedings of the 22nd ACM international conference on Information & Knowledge Management10.1145/2505515.2505543(519-528)Online publication date: 27-Oct-2013
  • (2012)Evaluating the effectiveness of search task trailsProceedings of the 21st international conference on World Wide Web10.1145/2187836.2187903(489-498)Online publication date: 16-Apr-2012
  • (2008)Learning user interests for a session-based personalized searchProceedings of the second international symposium on Information interaction in context10.1145/1414694.1414708(57-64)Online publication date: 14-Oct-2008
  • (2006)WebKDD 2006ACM SIGKDD Explorations Newsletter10.1145/1233321.12333348:2(84-89)Online publication date: 1-Dec-2006

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