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Titlebook: Analysing Web Traffic; A Case Study on Arti Agnieszka Jastrz?bska,Jan W. Owsiński,Tomasz Zwier Book 2023 The Editor(s) (if applicable) and

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發(fā)表于 2025-3-21 20:07:41 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Analysing Web Traffic
期刊簡稱A Case Study on Arti
影響因子2023Agnieszka Jastrz?bska,Jan W. Owsiński,Tomasz Zwier
視頻videohttp://file.papertrans.cn/157/156026/156026.mp4
發(fā)行地址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 methodologi
學(xué)科分類Studies in Big Data
圖書封面Titlebook: Analysing Web Traffic; A Case Study on Arti Agnieszka Jastrz?bska,Jan W. Owsiński,Tomasz Zwier Book 2023 The Editor(s) (if applicable) and
影響因子.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..
Pindex Book 2023
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沙發(fā)
發(fā)表于 2025-3-21 22:41:42 | 只看該作者
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發(fā)表于 2025-3-22 09:53:26 | 只看該作者
https://doi.org/10.1007/978-3-030-35234-9Having characterised the problem that we address and the way of acquiring data that we use, we now turn to the features, which can be extracted from the raw data, and the choice of the possibly good selection of a subset of these variables from the point of view of the problem at hand.
6#
發(fā)表于 2025-3-22 13:39:36 | 只看該作者
Digital Cultural TransformationWhen dealing with challenging, real-world datasets, one may turn to hybrid data processing approaches that join several kinds of data analysis algorithms. The hybrid data analysis techniques are popular in the literature, where we may find fusions of optimization and classification algorithms, clustering and classification algorithms.
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發(fā)表于 2025-3-22 20:04:01 | 只看該作者
https://doi.org/10.1007/978-3-030-83803-4The case study presented in this book highlights the properties and challenges of distinguishing bot and human traffic using weblogs and compares several solutions to this task. We present here, first, the observations related to the methodological side of the potential problem solution.
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發(fā)表于 2025-3-22 21:11:59 | 只看該作者
The Pragmatics of the Data Acquisition and Assessment,In this chapter, we will look in a more detail at the ways in which data were acquired and processed in the framework of the project in question. We will do so against the background of observations and examples already provided in the preceding section, starting with the first section of the present chapter.
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發(fā)表于 2025-3-23 02:01:24 | 只看該作者
The Proper Representation: Patterns, Variables and Their Analysis,Having characterised the problem that we address and the way of acquiring data that we use, we now turn to the features, which can be extracted from the raw data, and the choice of the possibly good selection of a subset of these variables from the point of view of the problem at hand.
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發(fā)表于 2025-3-23 09:14:41 | 只看該作者
The Hybrid Cluster-And-Classify Approach,When dealing with challenging, real-world datasets, one may turn to hybrid data processing approaches that join several kinds of data analysis algorithms. The hybrid data analysis techniques are popular in the literature, where we may find fusions of optimization and classification algorithms, clustering and classification algorithms.
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