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Online Mining of Web Usage Data: An Overview

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Web Mining Applications in E-commerce and E-services

Part of the book series: Studies in Computational Intelligence ((SCI,volume 172))

Abstract

In recent years, web usage mining techniques have helped online service providers to enhance their services, and restructure and redesign their websites in line with the insights gained. The application of these techniques is essential in building intelligent, personalised online services. More recently, it has been recognised that the shift from traditional to online services – and so the growing numbers of online customers and the increasing traffic generated by them – brings new challenges to the field. Highly demanding real-world E-commerce and E-services applications, where the rapid, and possibly changing, large volume data streams do not allow offline processing, motivate the development of new, highly efficient real-time web usage mining techniques. This chapter provides an introduction to online web usage mining and presents an overview of the latest developments. In addition, it outlines the major, and yet mostly unsolved, challenges in the field.

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Authors and Affiliations

  1. Department of Computer Science, VU University Amsterdam, De Boelelaan 1081A, 1081 HV, Amsterdam, The Netherlands

    Peter I. Hofgesang

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  1. Peter I. Hofgesang
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  1. Department of Information Management , University of Kaohsiung, Kaohsiung, Taiwan

    I-Hsien Ting

  2. National Changhua, University of Education , Taiwan

    Hui-Ju Wu

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Hofgesang, P.I. (2009). Online Mining of Web Usage Data: An Overview. In: Ting, IH., Wu, HJ. (eds) Web Mining Applications in E-commerce and E-services. Studies in Computational Intelligence, vol 172. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88081-3_1

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