Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data

Web mining aims to discover useful information and knowledge from Web hyperlinks, page contents, and usage data. Although Web mining uses many conventional data mining techniques, it is not purely an application of traditional data mining due to the semi-structured and unstructured nature of the Web...

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Tác giả chính:	Bing, Liu
Định dạng:	Sách
Ngôn ngữ:	English
Được phát hành:	Springer Berlin Heidelberg 2014
Những chủ đề:	Information Storage and Retrieval Data Mining and Knowledge Discovery Pattern Recognition
Truy cập trực tuyến:	https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/37726
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spelling	oai:scholar.dlu.edu.vn:DLU123456789-377262023-11-11T05:06:50Z Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data Bing, Liu Information Storage and Retrieval Data Mining and Knowledge Discovery Pattern Recognition Web mining aims to discover useful information and knowledge from Web hyperlinks, page contents, and usage data. Although Web mining uses many conventional data mining techniques, it is not purely an application of traditional data mining due to the semi-structured and unstructured nature of the Web data. The field has also developed many of its own algorithms and techniques. Liu has written a comprehensive text on Web mining, which consists of two parts. The first part covers the data mining and machine learning foundations, where all the essential concepts and algorithms of data mining and machine learning are presented. The second part covers the key topics of Web mining, where Web crawling, search, social network analysis, structured data extraction, information integration, opinion mining and sentiment analysis, Web usage mining, query log mining, computational advertising, and recommender systems are all treated both in breadth and in depth. His book thus brings all the related concepts and algorithms together to form an authoritative and coherent text. The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in Web mining and data mining both as a learning text and as a reference book. Professors can readily use it for classes on data mining, Web mining, and text mining. Additional teaching materials such as lecture slides, datasets, and implemented algorithms are available online. 2014-06-12T06:28:08Z 2014-06-12T06:28:08Z 2011 Book 978-3-642-19459-7 978-3-642-19460-3 https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/37726 en Data-Centric Systems and Applications application/pdf Springer Berlin Heidelberg
institution	Thư viện Trường Đại học Đà Lạt
collection	Thư viện số
language	English
topic	Information Storage and Retrieval Data Mining and Knowledge Discovery Pattern Recognition
spellingShingle	Information Storage and Retrieval Data Mining and Knowledge Discovery Pattern Recognition Bing, Liu Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data
description	Web mining aims to discover useful information and knowledge from Web hyperlinks, page contents, and usage data. Although Web mining uses many conventional data mining techniques, it is not purely an application of traditional data mining due to the semi-structured and unstructured nature of the Web data. The field has also developed many of its own algorithms and techniques. Liu has written a comprehensive text on Web mining, which consists of two parts. The first part covers the data mining and machine learning foundations, where all the essential concepts and algorithms of data mining and machine learning are presented. The second part covers the key topics of Web mining, where Web crawling, search, social network analysis, structured data extraction, information integration, opinion mining and sentiment analysis, Web usage mining, query log mining, computational advertising, and recommender systems are all treated both in breadth and in depth. His book thus brings all the related concepts and algorithms together to form an authoritative and coherent text. The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in Web mining and data mining both as a learning text and as a reference book. Professors can readily use it for classes on data mining, Web mining, and text mining. Additional teaching materials such as lecture slides, datasets, and implemented algorithms are available online.
format	Book
author	Bing, Liu
author_facet	Bing, Liu
author_sort	Bing, Liu
title	Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data
title_short	Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data
title_full	Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data
title_fullStr	Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data
title_full_unstemmed	Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data
title_sort	web data mining: exploring hyperlinks, contents, and usage data
publisher	Springer Berlin Heidelberg
publishDate	2014
url	https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/37726
_version_	1782535793045143552

Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data

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