- 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
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- Über dieses Buch
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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.
- Inhaltsverzeichnis (14 Kapitel)
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An Introduction to Text Mining
Seiten 1-10
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Information Extraction from Text
Seiten 11-41
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A Survey of Text Summarization Techniques
Seiten 43-76
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A Survey of Text Clustering Algorithms
Seiten 77-128
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Dimensionality Reduction and Topic Modeling: From Latent Semantic Indexing to Latent Dirichlet Allocation and Beyond
Seiten 129-161
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Inhaltsverzeichnis (14 Kapitel)
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- Download Inhaltsverzeichnis PDF (127.1 KB)
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Bibliografische Information
- Bibliographic Information
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- Buchtitel
- Mining Text Data
- Herausgeber
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- Charu C. Aggarwal
- ChengXiang Zhai
- Copyright
- 2012
- Verlag
- Springer-Verlag New York
- Copyright Inhaber
- Springer Science+Business Media, LLC
- eBook ISBN
- 978-1-4614-3223-4
- DOI
- 10.1007/978-1-4614-3223-4
- Hardcover ISBN
- 978-1-4614-3222-7
- Softcover ISBN
- 978-1-4899-8920-8
- Auflage
- 1
- Seitenzahl
- XII, 524
- Themen
