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Information Retrieval

, Volume 14, Issue 2, pp 208–211 | Cite as

Michael W. Berry and Jacob Kogan (eds.): Text mining: applications and theory

John Wiley and Sons, Ltd, 2010, xiv + 207 pp, £55.00/€66.00, hardcover, ISBN: 978-0-470-74982-1
  • Zhang Xiaojun
Book Review

Text mining: applications and theorypresents the state-of-the-art algorithms for text mining from both the academic and industrial perspectives. Actually, it is the proceedings of a one-day workshop on text mining which hold on May 2, 2009 in conjunction with the SIAM Ninth International Conference on Data 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” (p. xiv). Collectively, the contributors span several major topic areas in text mining: Keyword extraction, Classification and clustering, Anomaly and trend detection, Text streams. According to these topic areas, Michael W. Berry and Jacob Kogan divided the content into three parts: Part I, Text Extraction, Classification and Clustering (Chaps. 1–5); Part II, Anomaly and...

References

  1. Berry, M. W. (Ed.). (2003). Survey of text mining. New York, USA: Springer.Google Scholar
  2. Srivastava, A. N., & Sahami, M. (Eds.). (2009). Text mining. Boca Raton, USA: CRC Press.MATHGoogle Scholar
  3. Weiss, S. M., et al. (Eds.). (2005). Text mining. New York, USA: Springer.MATHGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.School of Foreign LanguagesShaanxi Normal UniversityXi’anChina

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