Determining the Time Window Threshold to Identify User Sessions of Stakeholders of a Commercial Bank Portal | Zendy

Jozef Kapusta | Zendy; Michal Munk | Zendy; Peter Švec | Zendy; Anna Pilková | Zendy

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Determining the Time Window Threshold to Identify User Sessions of Stakeholders of a Commercial Bank Portal

Author(s) -

Jozef Kapusta,

Michal Munk,

Peter Švec,

Anna Pilková

Publication year - 2014

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2014.05.163

Subject(s) - computer science , session (web analytics) , quartile , identification (biology) , window (computing) , range (aeronautics) , focus (optics) , threshold limit value , variable (mathematics) , data mining , statistics , world wide web , mathematics , confidence interval , medicine , mathematical analysis , botany , materials science , physics , environmental health , optics , composite material , biology

In this paper, we focus on finding the suitable value of the time threshold, which is then used in the method of user session identification based on the time. To determine its value, we used the Length variable representing the time a user spent on a particular site. We compared two values of time threshold with experimental methods of user session identification based on the structure of the web: Reference Length and H-ref. When comparing the usefulness of extracted rules using all four methods, we proved that the use of the time threshold calculated from the quartile range is the most appropriate method for identifying sessions for web usage mining

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