Natural Language Processing and Text Mining

By: Anne Kao (Editor), Steve R. Poteet (Editor)

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Paperback | 13 October 2010

At a Glance

Paperback
280 Pages

Dimensions(cm)
23.39 x 15.6 x 1.5

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$219.75

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The topic this book addresses originated from a panel discussion at the 2004 ACM SIGKDD (Special Interest Group on Knowledge Discovery and Data Mining) Conference held in Seattle, Washington, USA. We the editors or- nized the panel to promote discussion on how text mining and natural l- guageprocessing, tworelatedtopicsoriginatingfromverydi?erentdisciplines, can best interact with each other, and bene't from each other's strengths. It attracted a great deal of interest and was attended by 200 people from all over the world. We then guest-edited a special issue of ACM SIGKDD Exp- rations on the same topic, with a number of very interesting papers. At the same time, Springer believed this to be a topic of wide interest and expressed an interest in seeing a book published. After a year of work, we have put - gether 11 papers from international researchers on a range of techniques and applications. We hope this book includes papers readers do not normally ?nd in c- ference proceedings, which tend to focus more on theoretical or algorithmic breakthroughs but are often only tried on standard test data. We would like to provide readers with a wider range of applications, give some examples of the practical application of algorithms on real-world problems, as well as share a number of useful techniques.

Industry Reviews

From the reviews: "The papers in this book describe a range of natural language processing (NLP) techniques and applications, all originating from an ACM Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD) panel discussion. ! Overall, the contributions are well balanced with respect to the different approaches presented ! . The volume appears to serve its intended purpose, which is to provide an electric overview of the international research efforts in text mining, featuring relevant tools and techniques from NLP and machine learning." (Peter Jackson, Computing Reviews, March, 2008)

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