Logo - springer
Slogan - springer

Computer Science - Database Management & Information Retrieval | Web Data Mining - Exploring Hyperlinks, Contents, and Usage Data

Web Data Mining

Exploring Hyperlinks, Contents, and Usage Data

Liu, Bing

2nd ed. 2011, XX, 624 p.

Available Formats:
eBook
Information

Springer eBooks may be purchased by end-customers only and are sold without copy protection (DRM free). Instead, all eBooks include personalized watermarks. This means you can read the Springer eBooks across numerous devices such as Laptops, eReaders, and tablets.

You can pay for Springer eBooks with Visa, Mastercard, American Express or Paypal.

After the purchase you can directly download the eBook file or read it online in our Springer eBook Reader. Furthermore your eBook will be stored in your MySpringer account. So you can always re-download your eBooks.

 
$39.99

(net) price for USA

ISBN 978-3-642-19460-3

digitally watermarked, no DRM

Included Format: PDF

download immediately after purchase


learn more about Springer eBooks

add to marked items

Hardcover
Information

Hardcover version

You can pay for Springer Books with Visa, Mastercard, American Express or Paypal.

Standard shipping is free of charge for individual customers.

 
$59.95

(net) price for USA

ISBN 978-3-642-19459-7

free shipping for individuals worldwide

usually dispatched within 3 to 5 business days


add to marked items

Softcover
Information

Softcover (also known as softback) version.

You can pay for Springer Books with Visa, Mastercard, American Express or Paypal.

Standard shipping is free of charge for individual customers.

 
$59.95

(net) price for USA

ISBN 978-3-642-26891-5

free shipping for individuals worldwide

usually dispatched within 3 to 5 business days


add to marked items

  • Covers all key tasks and techniques of Web search and Web mining, i.e., structure mining, content mining, and usage mining
  • Includes major algorithms from data mining, machine learning, information retrieval and text processing, which are crucial for many Web mining tasks
  • Contains a rich blend of theory and practice, addressing seminal research ideas and also looking at the technology from a practical point of view
  • Second edition includes new/revised sections on supervised learning, opinion mining and sentiment analysis, recommender systems and collaborative filtering, and query log mining
  • Ideally suited for classes on data mining, Web mining, Web search, and knowledge discovery in data bases
  • Provides internet support with lecture slides and project problems

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.

Content Level » Graduate

Keywords » Information Integration - Information Retrieval - Machine Learning - Opinion Mining - Pattern Mining - Recommender Systems - Schema Matching - Semi-Supervised Learning - Social Network Analysis - Structured Data Extraction - Unsupervised Learning - Web Crawling - Web Data Mining - Web Link Analysis - Web Search - Web Usage Mining - Wrapper Generation

Related subjects » Artificial Intelligence - Database Management & Information Retrieval - Image Processing - Physical & Information Science

Table of contents / Sample pages 

Popular Content within this publication 

 

Articles

Read this Book on Springerlink

Services for this book

New Book Alert

Get alerted on new Springer publications in the subject area of Information Storage and Retrieval.