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Web Mining

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Submitted By realyeti
Words 797
Pages 4
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By Daniel Nunez
Nov 23, 2014

WEB MINING A. INTRODUCTION
The abundant data present in the World Wide Web (web for short) through the internet is vast on useful information. User-specific information of how they interact with the Web and system-specific data of how the Web is structured as more and more bytes of information get uploaded and shared through the Web are examples of how there is vital information to be studied and reflected upon with the means of finding deep, valuable, new knowledge that could potentially make numerous computer enterprises increasingly effective.
The “figuring out” of what is relevant, yet unknown in large sets of data through observation and analysis is the task of data mining. Data mining relies on sophisticated approaches and methods, such as artificial intelligence, statistical deduction and induction, information retrieval and natural language processing (NLP) [2], of going through large amount of organized or unorganized data to find “capitalizeable” patterns and potentially useful information.
With this preliminary description of data mining partial intricacies, I proceed to define Web mining as the application of data mining practices to search and find, filter, extract and assess [4] Web data to better understand its contents, structure, usage[1][2][3][4] and processes[4]. Web mining practices have been classified between three qualitative categories: Web content, Web structure, and Web usage [1][2][3][4]. With each category working with different types of data and employing different kind of analyses techniques. Among literature, it is also common to find Web data mining practices are based on two different views: a “process-centric” view and a “data-centric” view[4]. These categories encompass the various kinds of stacked information “sitting” on databases waiting to be analyzed and exploited based

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