Covers Text Embedded with Heterogeneous and Multimedia Data
All chapters contain a comprehensive survey including the key research content on the topic, and the future directions of research in the field
This book simplifies the content, so that advanced-level students, practitioners and researchers in computer science can benefit from it
Includes supplementary material: sn.pub/extras
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Table of contents (14 chapters)
About this book
Text mining applications have experienced tremendous advances because of web 2.0 and social networking applications. Recent advances in hardware and software technology have lead to a number of unique scenarios where text mining algorithms are learned.
Mining Text Data introduces an important niche in the text analytics field, and is an edited volume contributed by leading international researchers and practitioners focused on social networks & data mining. This book contains a wide swath in topics across social networks & data mining. Each chapter contains a comprehensive survey including the key research content on the topic, and the future directions of research in the field. There is a special focus on Text Embedded with Heterogeneous and Multimedia Data which makes the mining process much more challenging. A number of methods have been designed such as transfer learning and cross-lingual mining for such cases.
Mining Text Data simplifies the content, so that advanced-level students, practitioners and researchers in computer science can benefit from this book. Academic and corporate libraries, as well as ACM, IEEE, and Management Science focused on information security, electronic commerce, databases, data mining, machine learning, and statistics are the primary buyers for this reference book.
- Data mining
- Machine learning and e-commerce
- Mining text
- Multimedia data
- Networking applications
- Social networks
- Text mining
Editors and Affiliations
Thomas J. Watson Research Center, IBM, Hawthorne, USA
Charu C. Aggarwal
at Urbana-Champaign, University of Illinois, URBANA, USA
Book Title: Mining Text Data
Editors: Charu C. Aggarwal, ChengXiang Zhai
Publisher: Springer New York, NY
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Science+Business Media, LLC 2012
Hardcover ISBN: 978-1-4614-3222-7Published: 03 February 2012
Softcover ISBN: 978-1-4899-8920-8Published: 12 April 2014
eBook ISBN: 978-1-4614-3223-4Published: 03 February 2012
Edition Number: 1
Number of Pages: XII, 524
Topics: Database Management, Data Mining and Knowledge Discovery, Computer and Information Systems Applications, Computer Communication Networks, Multimedia Information Systems