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A New Insight on the Morphology of Web Mining

A New Insight on the Morphology of Web Mining
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Author(s): Joshua Ojo Nehinbe (Federal University, Oye, Nigeria)
Copyright: 2022
Pages: 20
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.ch015

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Abstract

Recent surveys have revealed that about 199 million of active and over 1.2 Billion of inactive websites exist across the globe. The categories of websites have also increased beyond espionage networks of spies, computer networks for corporate organizations, networks for governments' agencies, networks for social interactions, search engines and networks for religious bodies, etc. These diversities have generated complex issues regarding the morphology and classification of webs and web mining. Thus, the validity of the generic web classification, web mining taxonomy, and contemporary studies on the regularities of web usage, web content, web semantic, web structures, and the process of extracting useful information and interesting patterns from the intricate of the Internet are frequently questionable. The existing web mining taxonomy can also lead to misinformation, misclassification, and crisscrossed issues such that numerous webs' patterns could be marked with crossing and inexplicable lines. By using qualitative virtual interviews of 26 skilled web-designers and a focus group-conference of 7 experts in web-usage to brainstorm on the above issues, this chapter comprehensively discusses the above concepts and how they relate to web classification and web mining taxonomy. The themes obtained elucidate the techniques that commonly underpin basic web mining taxonomy. New concepts like existence of esoteric web data, exoteric web data; mysterious, inexplicable, and mystifying patterns; and cryptic vocabularies are discussed to assist web analytics. Finally, the author suggests eight classification attributes for web mining patterns (illustrative, expositive, educative, advisory, interpretative, demonstrative, revealing, and informatory) and proposes a new web mining taxonomy to minimize the impacts of the above concerns on global settings.

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