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Classifying web search queries to identify high revenue generating customers

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  • Adan Ortiz-Cordova
  • Bernard J. Jansen

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  • Adan Ortiz-Cordova & Bernard J. Jansen, 2012. "Classifying web search queries to identify high revenue generating customers," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(7), pages 1426-1441, July.
    • Handle: RePEc:bla:jinfst:v:63:y:2012:i:7:p:1426-1441
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    File URL: http://hdl.handle.net/10.1002/asi.22640
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    References listed on IDEAS

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    1. Hui‐Min Chen & Michael D. Cooper, 2002. "Stochastic modeling of usage patterns in a web‐based information system," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 53(7), pages 536-548.
    2. Bernard J. Jansen & Soo Young Rieh, 2010. "The seventeen theoretical constructs of information searching and information retrieval," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(8), pages 1517-1534, August.
    3. Eric J. Johnson & Wendy W. Moe & Peter S. Fader & Steven Bellman & Gerald L. Lohse, 2004. "On the Depth and Dynamics of Online Search Behavior," Management Science, INFORMS, vol. 50(3), pages 299-308, March.
    4. Bernard J. Jansen & Soo Young Rieh, 2010. "The seventeen theoretical constructs of information searching and information retrieval," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(8), pages 1517-1534, August.
    5. Sugar, Catherine A. & James, Gareth M., 2003. "Finding the Number of Clusters in a Dataset: An Information-Theoretic Approach," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 750-763, January.
    6. Hui‐Min Chen & Michael D. Cooper, 2001. "Using clustering techniques to detect usage patterns in a Web‐based information system," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 52(11), pages 888-904.
    7. Tefko Saracevic, 1975. "RELEVANCE: A review of and a framework for the thinking on the notion in information science," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 26(6), pages 321-343, November.
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    Cited by:

    1. Stoehr, Niklas & Braesemann, Fabian & Zhou, Shi, 2019. "Mining the Automotive Industry: A Network Analysis of Corporate Positioning and Technological Trends," SocArXiv bu5zs, Center for Open Science.
    2. Damianos P. Sakas & Nikolaos Th. Giannakopoulos, 2021. "Harvesting Crowdsourcing Platforms’ Traffic in Favour of Air Forwarders’ Brand Name and Sustainability," Sustainability, MDPI, vol. 13(15), pages 1-25, July.
    3. repec:osf:socarx:bu5zs_v1 is not listed on IDEAS
    4. Klapdor, Sebastian & Anderl, Eva M. & von Wangenheim, Florian & Schumann, Jan H., 2014. "Finding the Right Words: The Influence of Keyword Characteristics on Performance of Paid Search Campaigns," Journal of Interactive Marketing, Elsevier, vol. 28(4), pages 285-301.

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