Text Mining and Visualization: Case Studies Using Open-Source Tools


Text Mining and Visualization: Case Studies Using Open-Source Tools (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series) 1st Edition
by Markus Hofmann, Andrew Chisholm (Editor)
Publisher finelybook 出版社:‏ Chapman and Hall/CRC; 1st edition (December 18, 2015)
Language 语言: English
Print Length 页数: 297 pages
ISBN-10: 1482237571
ISBN-13: 9781482237573

Book Description


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.

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