國立高雄大學圖資館 |

Analysing web traffica case study on artificial and genuine advertisement-related behaviour /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Analysing web trafficby Agnieszka Jastrzebska ... [et al.].
其他題名:	a case study on artificial and genuine advertisement-related behaviour /
其他作者:	Jastrzebska, Agnieszka.
出版者:	Cham :Springer Nature Switzerland :2023.
面頁冊數:	xx, 156 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Internet advertising.
電子資源:	https://doi.org/10.1007/978-3-031-32503-8
ISBN:	9783031325038$q(electronic bk.)

Analysing web traffica case study on artificial and genuine advertisement-related behaviour /
Analysing web traffica case study on artificial and genuine advertisement-related behaviour /[electronic resource] :by Agnieszka Jastrzebska ... [et al.]. - Cham :Springer Nature Switzerland :2023. - xx, 156 p. :ill. (some col.), digital ;24 cm. - Studies in big data,v. 1272197-6511 ;. - Studies in big data ;v.1..

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.

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.

ISBN: 9783031325038$q(electronic bk.)

Standard No.: 10.1007/978-3-031-32503-8doiSubjects--Topical Terms:

208231
Internet advertising.

LC Class. No.: HF6146.I58

Dewey Class. No.: 659.144

Analysing web traffica case study on artificial and genuine advertisement-related behaviour /
LDR:02745nmm a2200337 a 4500 001 647029
003 DE-He213
005 20230626102200.0
006 m d
007 cr nn 008maaau
008 240116s2023 sz s 0 eng d
020 $a 9783031325038$q(electronic bk.)
020 $a 9783031325021$q(paper)
024 7 $a 10.1007/978-3-031-32503-8 $2 doi
035 $a 978-3-031-32503-8
040 $a GP $c GP
041 0 $a eng
050 4 $a HF6146.I58
072 7 $a UN $2 bicssc
072 7 $a COM018000 $2 bisacsh
072 7 $a UN $2 thema
082 0 4 $a 659.144 $2 23
090 $a HF6146.I58 $b A532 2023
245 0 0 $a Analysing web traffic $h [electronic resource] : $b a case study on artificial and genuine advertisement-related behaviour / $c by Agnieszka Jastrzebska ... [et al.].
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2023.
300 $a xx, 156 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Studies in big data, $x 2197-6511 ; $v v. 127
505 0 $a 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.
520 $a 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.
650 0 $a Internet advertising. $3 208231
650 0 $a Internet marketing. $3 208232
650 0 $a Consumer behavior. $3 185170
650 1 4 $a Data Engineering. $3 839346
650 2 4 $a Computational Intelligence. $3 338479
650 2 4 $a Big Data. $3 760530
700 1 $a Jastrzebska, Agnieszka. $3 956178
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Studies in big data ; $v v.1. $3 675357
856 4 0 $u https://doi.org/10.1007/978-3-031-32503-8
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)