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Text Mining: Applications and Theory
Michael J A Berry
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Description for Text Mining: Applications and Theory
Hardcover. Text Mining: Applications and Theory presents the state-of-the-art algorithms for text mining from both the academic and industrial perspectives. Editor(s): Berry, Michael W.; Kogan, Jacob. Num Pages: 222 pages, Illustrations. BIC Classification: UNF. Category: (P) Professional & Vocational. Dimension: 236 x 162 x 18. Weight in Grams: 454.
Text Mining: Applications and Theory presents the state-of-the-art algorithms for text mining from both the academic and industrial perspectives. The contributors span several countries and scientific domains: universities, industrial corporations, and government laboratories, and demonstrate the use of techniques from machine learning, knowledge discovery, natural language processing and information retrieval to design computational models for automated text analysis and mining.
Text Mining: Applications and Theory presents the state-of-the-art algorithms for text mining from both the academic and industrial perspectives. The contributors span several countries and scientific domains: universities, industrial corporations, and government laboratories, and demonstrate the use of techniques from machine learning, knowledge discovery, natural language processing and information retrieval to design computational models for automated text analysis and mining.
This volume demonstrates how advancements in the fields of applied mathematics, computer science, machine learning, and natural language processing can collectively capture, classify, and interpret words and their contexts. As suggested in the preface, text mining is needed when ... Read more
This book:
- Provides state-of-the-art algorithms and techniques for critical tasks in text mining applications, such as clustering, classification, anomaly and trend detection, and stream analysis.
- Presents a survey of text visualization techniques and looks at the multilingual text classification problem.
- Discusses the issue of cybercrime associated with chatrooms.
- Features advances in visual analytics and machine learning along with illustrative examples.
- Is accompanied by a supporting website featuring datasets.
Applied mathematicians, statisticians, practitioners and students in computer science, bioinformatics and engineering will find this book extremely useful.
Show LessProduct Details
Format
Hardback
Publication date
2010
Publisher
John Wiley & Sons Inc United States
Number of pages
222
Condition
New
Number of Pages
224
Place of Publication
New York, United States
ISBN
9780470749821
SKU
V9780470749821
Shipping Time
Usually ships in 7 to 11 working days
Ref
99-50
About Michael J A Berry
Michael W. Berry, Professor and Associate Department Head, Department of Electrical Engineering and Computer Science, University of Tennessee. Michael is on the Editorial board of Computing in Science and Engineering and Statistical Analysis and Data Mining Journals. Jacob Kogan, Department of Mathematics and Statistics, University of Maryland Baltimore County, USA.
Reviews for Text Mining: Applications and Theory
"It is extremely useful for practitioners and students in computer science, natural language processing, bioinformatics and engineering who wish to use text mining techniques." (Journal of Information Retrieval, 1 April 2011)