Overview
- Presents an ample, richly illustrated account on the analysis of data concerning behavior patterns on the Web
- Provides a rich bibliography on the main problem approached and on the various methodologies tried out
- Gives a full-fledged report from a wide range of analytic and design efforts
Part of the book series: Studies in Big Data (SBD, volume 127)
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About this book
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.
Keywords
Table of contents (7 chapters)
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Front Matter
Authors and Affiliations
Bibliographic Information
Book Title: Analysing Web Traffic
Book Subtitle: A Case Study on Artificial and Genuine Advertisement-Related Behaviour
Authors: Agnieszka Jastrzębska, Jan W. Owsiński, Karol Opara, Marek Gajewski, Olgierd Hryniewicz, Mariusz Kozakiewicz, Sławomir Zadrożny, … Tomasz Zwierzchowski
Series Title: Studies in Big Data
DOI: https://doi.org/10.1007/978-3-031-32503-8
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
Hardcover ISBN: 978-3-031-32502-1Published: 27 June 2023
Softcover ISBN: 978-3-031-32505-2Published: 28 June 2024
eBook ISBN: 978-3-031-32503-8Published: 26 June 2023
Series ISSN: 2197-6503
Series E-ISSN: 2197-6511
Edition Number: 1
Number of Pages: XX, 156
Number of Illustrations: 5 b/w illustrations, 90 illustrations in colour
Topics: Data Engineering, Computational Intelligence, Big Data