Text Mining: Applications and Theory

Berry, Michael W.; Kogan, Jacob

ISBN 10: 0470749822 / ISBN 13: 9780470749821

Editore: Wiley (edition 1), 2010

It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting. Codice articolo 0470749822-11-1

Riassunto:

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 “words are not enough.”

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.

Informazioni sull'autore:

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.

Dati bibliografici

Titolo: Text Mining: Applications and Theory
Casa editrice: Wiley (edition 1)
Data di pubblicazione: 2010
Legatura: Hardcover
Condizione: Very Good
Edizione: 1.