Analysing Web Traffic [[electronic resource] ] : A Case Study on Artificial and Genuine Advertisement-Related Behaviour / / by Agnieszka Jastrzębska, Jan W. Owsiński, Karol Opara, Marek Gajewski, Olgierd Hryniewicz, Mariusz Kozakiewicz, Sławomir Zadrożny, Tomasz Zwierzchowski

• Autore: Jastrzębska Agnieszka
• Pubblicazione: Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
• Edizione: 1st ed. 2023.
• Descrizione fisica: 1 online resource (173 pages)
• Disciplina: 659.144
• Soggetto topico: Engineering—Data processing; Computational intelligence; Big data; Data Engineering; Computational Intelligence; Big Data
• Altri autori: OwsińskiJan W OparaKarol GajewskiMarek HryniewiczOlgierd KozakiewiczMariusz ZadrożnySławomir ZwierzchowskiTomasz
• Nota di contenuto: The problem and its key characteristics -- The pragmatics of the data acquisition and assessment -- The proper representation: patterns, variables and their analysis -- Clustering analysis -- Building the classifiers -- The hybrid cluster-and-classify approach -- A summary view of the problem and its solution.
• Sommario/riassunto: This book presents ample, richly illustrated account on results and experience from a project, dealing with the analysis of data concerning behavior patterns on the Web. The advertising on the Web is dealt with, and the ultimate issue is to assess the share of the artificial, automated activity (ads fraud), as opposed to the genuine human activity. After a comprehensive introductory part, a full-fledged report is provided from a wide range of analytic and design efforts, oriented at: the representation of the Web behavior patterns, formation and selection of telling variables, structuring of the populations of behavior patterns, including the use of clustering, classification of these patterns, and devising most effective and efficient techniques to separate the artificial from the genuine traffic. A series of important and useful conclusions is drawn, concerning both the nature of the observed phenomenon, and hence the characteristics of the respective datasets, and the appropriateness of the methodological approaches tried out and devised. Some of these observations and conclusions, both related to data and to methods employed, provide a new insight and are sometimes surprising. The book provides also a rich bibliography on the main problem approached and on the various methodologies tried out.
• Titolo autorizzato: Analysing Web Traffic
• ISBN: 3-031-32503-6
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910746093603321
• Lo trovi qui: Univ. Federico II
• Serie: Studies in Big Data, . 2197-6511 ; ; 127