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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-explain...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Boca Raton :
Chapman & Hall/CRC,
2016.
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| Edición: | 1st. |
| Colección: | Chapman & Hall/CRC data mining and knowledge discovery series.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 245 | 0 | 0 | |a Text mining and visualization : |b case studies using open-source tools / |c edited by Markus Hofmann, Andrew Chisholm. |
| 250 | |a 1st. | ||
| 264 | 4 | |c ©2016 | |
| 264 | 1 | |a Boca Raton : |b Chapman & Hall/CRC, |c 2016. | |
| 300 | |a 1 online resource : |b illustrations (black and white). | ||
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| 588 | 0 | |a CIP data; item not viewed. | |
| 505 | 0 | |a Front Cover; Contents; I: RapidMiner; 1. RapidMiner for Text Analytic Fundamentals; 2. Empirical Zipf-Mandelbrot Variation for Sequential Windows within Documents; II: KNIME; 3. Introduction to the KNIME Text Processing Extension; 4. Social Media Analysis -- Text Mining Meets Network Mining; III: Python; 5. Mining Unstructured User Reviews with Python; 6. Sentiment Classification and Visualization of Product Review Data; 7. Mining Search Logs for Usage Patterns; 8. Temporally Aware Online News Mining and Visualization with Python; 9. Text Classification Using Python; IV: R. | |
| 505 | 8 | |a 10. Sentiment Analysis of Stock Market Behavior from Twitter Using the R Tool11. Topic Modeling; 12. Empirical Analysis of the Stack Overflow Tags Network; Back Cover. | |
| 504 | |a Includes bibliographical references and index. | ||
| 520 | |a 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 w. | ||
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| 650 | 0 | |a Data mining. | |
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| 650 | 6 | |a Exploration de données (Informatique) | |
| 650 | 7 | |a Data mining. |2 fast |0 (OCoLC)fst00887946 | |
| 700 | 1 | |a Hofmann, Markus |c (Computer scientist), |e editor. | |
| 700 | 1 | |a Chisholm, Andrew, |e editor. | |
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| 830 | 0 | |a Chapman & Hall/CRC data mining and knowledge discovery series. | |
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