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Web Mining and Web Usage Mining for Various Human-Driven Applications

Web Mining and Web Usage Mining for Various Human-Driven Applications
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Author(s): Avinash Kumar (School of Engineering and Technology, Sharda University, India), Bharat Bhushan (School of Engineering and Technology, Sharda University, India.), Nandita Pokhriya (School of Engineering and Technology, Sharda University), Raj Chaganti (Department of Computer Science, University of Texas at San Antonio, USA) and Parma Nand (School of Engineering and Technology, Sharda University, India)
Copyright: 2022
Pages: 25
Source title: Advanced Practical Approaches to Web Mining Techniques and Application
Source Author(s)/Editor(s): Ahmed J. Obaid (University of Kufa, Iraq), Zdzislaw Polkowski (Wroclaw University of Economics, Poland) and Bharat Bhushan (Sharda University, India)
DOI: 10.4018/978-1-7998-9426-1.ch007

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Abstract

The current century has seen a huge amount of data being produced every day by various computational platforms. These data are very large in amount when compared to the past. These data have emerged in form of big data (BD), and it's vital to manage these data for processing as well as extracting. The big data are emerging from Facebook, Instagram, and various other social as well as private platforms. Web mining has the capabilities to mine or extract data from a very huge set of data. The mining of useful information is essential for optimal functioning of various systems. In this chapter, the usage of web mining and one of its sub categories, web usage mining, for various human-driven applications has been discussed. This chapter focuses on the background that leads to the emergence of web mining. The chapter also deeply explores various subdomains that are essential for tackling data extraction using web mining.

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