| Feature | Text Mining | Text Analytics |
|---|---|---|
| Definition | Extracting insights from unstructured text using statistical and ML techniques. | Analyzing text data for actionable insights. |
| Focus | Identifying patterns and trends in large text datasets. | Deriving insights to make informed decisions. |
| Techniques | NLP, ML, information retrieval, data mining. | Sentiment analysis, entity recognition, summarization. |
| Applications | Document clustering, classification, topic modeling. | Customer feedback analysis, fraud detection. |
| Output | Clusters, classification labels, topic models. | Actionable insights and recommendations. |
| Scope | Revealing hidden knowledge in text data. | Combining technical skills with business understanding. |
| Tools | R, Python, NLTK, spaCy. | Specialized software, platforms, cloud services. |
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