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Text mining and visualization : case studies using open-source tools

Author: Markus Hofmann, (Computer scientist); Andrew Chisholm
Publisher: Boca Raton : CRC Press, [2016] ©2016
Series: Chapman & Hall/CRC data mining and knowledge discovery series.
Edition/Format:   Print book : EnglishView all editions and formats
Summary:
"Text Mining and Visualization: Case Studies Using Open-Source Tools provides an introduction to text mining using some of the most popular and powerful open-source tools: KNIME, RapidMiner, Weka, R, and Python. The contributors - all highly experienced with text mining and open-source software - explain how text data are gathered and processed from a wide variety of sources, including books, server access logs,  Read more...
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Document Type: Book
All Authors / Contributors: Markus Hofmann, (Computer scientist); Andrew Chisholm
ISBN: 1482237571 9781482237573
OCLC Number: 911801405
Notes: "A Champman & Hall Book."
Description: xl, 297 pages, 10 unnumbered pages of plates : illustrations ; 26 cm.
Contents: RapidMiner for text analytic fundamentals / John Ryan --
Empirical Zipf-Mandelbrot variation for sequential windows within documents / Andrew Chisholm --
Introduction to the KNIME text processing extention / Kilian Thiel --
Social media analysis --
text mining meets network mining / Kilian Thiel, Tobias Kötter, Rosaria Silipo, and Phil Winters --
Mining unstructured user reviews with Python / Brian Carter --
Sentiment classification and visualization of product review data / Alexander Piazza and Pavlina Davcheva --
Mining search logs for usage patterns / Tony Russell-Rose and Paul Clough --
Temporally aware online news mining and visualization with Python / Kyle Goslin --
Text classification using Python / David Colton --
Sentiment analysis of stock market behavior from Twitter using the R tool / Nun Oliverira, Paulo Cortez, and Nelson Areal --
Topic modeling / Patrick Buckley --
Empiricial analysis of the stack overflow tags network / Christos Iraklis Tsatsoulis.
Series Title: Chapman & Hall/CRC data mining and knowledge discovery series.
Responsibility: edited by Markus Hofmann, Andrew Chisholm.

Abstract:

"Text Mining and Visualization: Case Studies Using Open-Source Tools provides an introduction to text mining using some of the most popular and powerful open-source tools: KNIME, RapidMiner, Weka, R, and Python. The contributors - all highly experienced with text mining and open-source software - explain how text data are gathered and processed from a wide variety of sources, including books, server access logs, websites, social media sites, and message boards. Each chapter presents a case study that you can follow as part of a step-by-step, reproducible example. You can also easily apply and extend the techniques to other problems. All the examples are available on a supplementary website. The book shows you how to exploit your text data, offering successful application examples and blueprints for you to tackle your text mining tasks and benefit from open and freely available tools. It gets you up to date on the latest and most powerful tools, the data mining process, and specific text mining activities"--Back cover.

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"The timing of this book could not be better. It focuses on text mining, text being one of the data sources still to be truly harvested, and on open-source tools for the analysis and visualization of Read more...

 
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