Original title: Clickstream Analysis
Authors: Kliegr, Tomáš ; Rauch, Jan (advisor) ; Berka, Petr (referee)
Document type: Master’s theses
Year: 2007
Language: cze
Publisher: Vysoká škola ekonomická v Praze
Abstract: Thesis introduces current research trends in clickstream analysis and proposes a new heuristic that could be used for dimensionality reduction of semantically enriched data in Web Usage Mining (WUM). Click-fraud and conversion fraud are identified as key prospective application areas for WUM. Thesis documents a conversion fraud vulnerability of Google Analytics and proposes defense - a new clickstream acquisition software, which collects data in sufficient granularity and structure to allow for data mining approaches to fraud detection. Three variants of K-means clustering algorithms and three association rule data mining systems are evaluated and compared on real-world web usage data.
Keywords: clickstream; Data mining; Dimensionality reduction; GUHA; Web Usage Mining

Institution: University of Economics, Prague (web)
Document availability information: Available in the digital repository of the University of Economics, Prague.
Original record: http://www.vse.cz/vskp/eid/3808

Permalink: http://www.nusl.cz/ntk/nusl-2065


The record appears in these collections:
Universities and colleges > Public universities > University of Economics, Prague
Academic theses (ETDs) > Master’s theses