========================
Text Classification
========================

Text classification is a fundamental NLP task that assigns predefined categories to text instances. It is widely applied in multiple scenarios:

- **Sentiment analysis**: Determine emotional polarity (positive/negative/neutral) in reviews or comments
- **Topic labeling**: Categorize news articles or documents by subject
- **Spam detection**: Identify unsolicited emails/messages
- **Intent recognition**: Classify user queries in dialog systems
- **Question answering**: Determine answerability of questions

Key technical challenges include:
1. Variable text lengths (from phrases to documents)
2. Multilingual and cross-domain generalization
3. Discrepancies in label systems across domains
4. Class imbalance issues

Common solutions involve:
- Data cleaning and preprocessing
- Feature engineering (TF-IDF, embeddings)
- Model selection (from traditional ML to deep learning)
- Hyperparameter tuning and ensemble methods