Practical Text Analytics Maximizing the Value of Text Data /
| Autors principals: | , , |
|---|---|
| Autor corporatiu: | |
| Sumari: | XXVIII, 285 p. 265 illus., 157 illus. in color. text |
| Idioma: | anglès |
| Publicat: |
Cham :
Springer International Publishing : Imprint: Springer,
2019.
|
| Edició: | 1st ed. 2019. |
| Col·lecció: | Advances in Analytics and Data Science,
2 |
| Matèries: | |
| Accés en línia: | https://doi.org/10.1007/978-3-319-95663-3 |
| Format: | Electrònic Llibre |
Taula de continguts:
- Chapter 1. Introduction to Text Analytics
- Chapter 2. Fundamentals of Content Analysis
- Chapter 3. Text Analytics Roadmap
- Chapter 4. Text Pre-Processing
- Chapter 5. Term-Document Representation
- Chapter 6. Semantic Space Representation and Latent Semantic Analysis
- Chapter 7. Cluster Analysis: Modeling Groups in Text
- Chapter 8. Probabilistic Topic Models
- Chapter 9. Classification Analysis: Machine Learning Applied to Text
- Chapter 10. Modeling Text Sentiment: Learning and Lexicon Models
- Chapter 11. Storytelling Using Text Data
- Chapter 12. Visualizing Results
- Chapter 13. Sentiment Analysis of Movie Reviews using R
- Chapter 14. Latent Semantic Analysis (LSA) in Python
- Chapter 15. Learning-Based Sentiment Analysis using RapidMiner
- Chapter 16. SAS Visual Text Analytics.