How does Tatar Text Summarizer work?
- Natural Language Processing (NLP). NLP techniques analyze the structure and meaning of the Tatar text, enabling accurate summarization.
- TextRank Algorithm. This algorithm ranks sentences based on their importance and relevance, allowing the summarizer to extract the most significant parts.
- Clustering. Clustering groups similar concepts within texts to ensure that the summary represents the overall theme effectively.
- Machine Learning. Machine learning models are trained on large datasets to improve the accuracy and quality of generated summaries over time.