Analysing Web Traffic: A Case Study on Artificial and Genuine Advertisement-Related Behaviour: 127 (Studies in Big Data, 127) - Softcover

Jastrzębska, Agnieszka; Owsiński, Jan W.; Opara, Karol; Gajewski, Marek; Hryniewicz, Olgierd; Kozakiewicz, Mariusz; Zadrożny, Sławomir; Zwierzchowski, Tomasz

Softcover

ISBN 10: 3031325052 ISBN 13: 9783031325052

Publisher: Springer, 2024

Synopsis

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 theappropriateness 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.

About this title

From the Back Cover

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 theappropriateness 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.

Edition details

• Publisher: Springer
• Publication date: 2024
• Language: English
• ISBN 10: 3031325052
• ISBN 13: 9783031325052
• Binding: Paperback
• Number of pages: 176