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
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| Other Authors: | , |
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| Format: | Book |
| Language: | English |
| Published: |
Boca Raton, FL
CRC Press
[2016]
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| Series: | Chapman & Hall/CRC data mining and knowledge discovery series
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| Subjects: | |
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Table of 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. 10. Sentiment Analysis of Stock Market Behavior from Twitter Using the R Tool11. Topic Modeling; 12. Empirical Analysis of the Stack Overflow Tags Network