Název:
Clickstream Analysis
Autoři:
Kliegr, Tomáš ; Rauch, Jan (vedoucí práce) ; Berka, Petr (oponent) Typ dokumentu: Diplomové práce
Rok:
2007
Jazyk:
cze
Nakladatel: Vysoká škola ekonomická v Praze
Abstrakt: 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.
Klíčová slova:
clickstream; Data mining; Dimensionality reduction; GUHA; Web Usage Mining
Instituce: Vysoká škola ekonomická v Praze
(web)
Informace o dostupnosti dokumentu:
Dostupné v digitálním repozitáři VŠE. Původní záznam: http://www.vse.cz/vskp/eid/3808