Text Mining: Applications and Theory
ISBN-13:
9780470749821
ISBN-10:
0470749822
Edition:
1
Author:
Michael W. Berry, Jacob Kogan
Publication date:
2010
Publisher:
Wiley
Format:
Hardcover
224 pages
Category:
Applied
,
Mathematics
FREE US shipping
Book details
ISBN-13:
9780470749821
ISBN-10:
0470749822
Edition:
1
Author:
Michael W. Berry, Jacob Kogan
Publication date:
2010
Publisher:
Wiley
Format:
Hardcover
224 pages
Category:
Applied
,
Mathematics
Summary
Text Mining: Applications and Theory (ISBN-13: 9780470749821 and ISBN-10: 0470749822), written by authors
Michael W. Berry, Jacob Kogan, was published by Wiley in 2010.
With an overall rating of 3.8 stars, it's a notable title among other
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(Mathematics) books. You can easily purchase or rent Text Mining: Applications and Theory (Hardcover) from BooksRun,
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Description
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.
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