Text mining and visualization case studies using open-source tools

"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...

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Bibliographic Details
Other Authors: Hofmann, Markus (Computer scientist), editor (editor), Chisholm, Andrew, editor
Format: eBook
Language:Inglés
Published: Boca Raton, Florida : CRC Press [2016]
Edition:1st
Series:Chapman & Hall/CRC data mining and knowledge discovery series.
Subjects:
See on Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009652821506719
Description
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, 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.
Item Description:A Chapman and Hall book--title page.
Physical Description:1 online resource (337 p.)
Bibliography:Includes bibliographical references at the end of each chapters.
ISBN:9780429161971
9781482237580