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Titlebook: Web Data Mining; Exploring Hyperlinks Bing Liu Textbook 20071st edition Springer-Verlag Berlin Heidelberg 2007 Perl.Web Crawling.Web Data M

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書目名稱Web Data Mining
副標(biāo)題Exploring Hyperlinks
編輯Bing Liu
視頻videohttp://file.papertrans.cn/1022/1021471/1021471.mp4
概述Covers all key tasks and techniques of Web search and Web mining, i.e., structure mining, content mining, and usage mining.First book with such a comprehensive coverage.Includes major algorithms from
叢書名稱Data-Centric Systems and Applications
圖書封面Titlebook: Web Data Mining; Exploring Hyperlinks Bing Liu Textbook 20071st edition Springer-Verlag Berlin Heidelberg 2007 Perl.Web Crawling.Web Data M
描述The rapid growth of the Web in the last decade makes it the largest p- licly accessible data source in the world. Web mining aims to discover u- ful information or knowledge from Web hyperlinks, page contents, and - age logs. Based on the primary kinds of data used in the mining process, Web mining tasks can be categorized into three main types: Web structure mining, Web content mining and Web usage mining. Web structure m- ing discovers knowledge from hyperlinks, which represent the structure of the Web. Web content mining extracts useful information/knowledge from Web page contents. Web usage mining mines user access patterns from usage logs, which record clicks made by every user. The goal of this book is to present these tasks, and their core mining - gorithms. The book is intended to be a text with a comprehensive cov- age, and yet, for each topic, sufficient details are given so that readers can gain a reasonably complete knowledge of its algorithms or techniques without referring to any external materials. Four of the chapters, structured data extraction, information integration, opinion mining, and Web usage mining, make this book unique. These topics are not covered by exi
出版日期Textbook 20071st edition
關(guān)鍵詞Perl; Web Crawling; Web Data Mining; algorithms; data mining; learning; machine learning; web mining
版次1
doihttps://doi.org/10.1007/978-3-540-37882-2
isbn_ebook978-3-540-37882-2Series ISSN 2197-9723 Series E-ISSN 2197-974X
issn_series 2197-9723
copyrightSpringer-Verlag Berlin Heidelberg 2007
The information of publication is updating

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Opinion Miningver, opinion mining can also provide valuable information for placing advertisements in Web pages. If in a page people express positive opinions or sentiments on a product, it may be a good idea to place an ad of the product. However, if people express negative opinions about the product, it is prob
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Textbook 20071st editionat readers can gain a reasonably complete knowledge of its algorithms or techniques without referring to any external materials. Four of the chapters, structured data extraction, information integration, opinion mining, and Web usage mining, make this book unique. These topics are not covered by exi
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uments marked-up in XML. This book provides a detailed description of query languages, indexing strategies, ranking algorithms, presentation scenarios developed to access XML documents. Major advances in XML retrieval were seen from 2002 as a result of INEX, the Initiative for Evaluation of XML Retr
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and supported by the Board of Research in Nuclear Sciences (BRNS), Department of Atomic Energy(DAE), India. As many as 400 physicists and researchers attended the 22nd Symposium to discuss the latest advances in the field. A poster session was also organized to highlight the work and findings of you
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