Web mining

(redirected from Web structure mining)

Web mining

Analyzing a website or all of the Web. Web "usage" mining determines the navigation patterns of users on a site and is derived from the server logs. Web "structure" mining examines the link hierarchy of a site in order to improve navigation. Web "content" mining explores the data contained in related sites in order to provide better resources for visitors. See data mining and text mining.
Copyright © 1981-2019 by The Computer Language Company Inc. All Rights reserved. THIS DEFINITION IS FOR PERSONAL USE ONLY. All other reproduction is strictly prohibited without permission from the publisher.
References in periodicals archive ?
Web mining broadly classified into three: Web Content Mining, Web structure Mining, and Web Usage Mining [2], [3].
There is a wide range of Web mining, which is divided into Web usage mining, Web content mining and Web structure mining.
With respect to the main goal of analysis, web mining can be divided into three types: web content mining, web structure mining and web usage mining.
The author has organized the main body of his text in fourteen chapters devoted to social media, big data and social data, hypotheses in the era of big data, social big data applications, basic concepts in data mining, association rule mining, clustering, classification, prediction, web structure mining, web content mining, web access log mining, information extraction, and deep web mining, media mining, and scalability and outlier detection.
Web mining is divided into web content mining, web structure mining and web usage mining.
There are three main web mining categories from the used data viewpoint: Web content mining, Web structure mining and Web usage mining (Spiliopoulou, 1999; Kosala and Blockeel, 2000; Bing, 2007).
With plenty of examples to guide readers from the basics to advanced techniques Markov and Larose cover the basics of web structure mining, including information retrieval and web searches and hyperlink-based ranking, web content mining, including clustering, evaluating clustering and classification and web usage mining, including preprocessing, exploratory data analysis, and modeling for web usage mining through clustering, association and classification.
Lee, examines a specific type of Web data mining called Web structure mining. This approach is based on studying the architecture of links within the Web.