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User Segmentation Based on Finding Communities with Similar Behavior on the Web Site

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F10%3A86077713" target="_blank" >RIV/61989100:27240/10:86077713 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1109/WI-IAT.2010.288" target="_blank" >http://dx.doi.org/10.1109/WI-IAT.2010.288</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/WI-IAT.2010.288" target="_blank" >10.1109/WI-IAT.2010.288</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    User Segmentation Based on Finding Communities with Similar Behavior on the Web Site

  • Original language description

    Web log analysis can be helpful in gaining information about the usability of the web site, web performance, for marketing purposes, or for development of business intelligence tools in e-commerce systems. User segmentation is one of the problems solvedin marketing and e-commerce sphere. Various software was developed to support web analysis. However, most of them provide only information through the tools based on statistics. In this paper there is presented the automatic user segmentation (clustering) based on the similar user's behavior on the web site. The user's behavior and behavioral patterns are extracted using process mining techniques; further user segmentation is provided by finding communities with similar behavior through two-step hierarchical clustering.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2010

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology

  • ISBN

    978-1-4244-8482-9

  • ISSN

  • e-ISSN

  • Number of pages

    4

  • Pages from-to

    75-78

  • Publisher name

    IEEE Computer Society

  • Place of publication

    Los Alamitos, California

  • Event location

    Toronto, Canada

  • Event date

    Aug 31, 2010

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article