How does Uyghur Text Summarizer work?
- Extractive Summarization. This method identifies and extracts key sentences from the source text, ensuring that the most important information is highlighted.
- Abstractive Summarization. Unlike extractive methods, abstractive summarization generates new sentences to convey the main ideas, allowing for more coherent and concise summaries.
- Machine Learning Algorithms. This approach employs sophisticated machine learning algorithms to learn patterns and relationships in the data, enhancing the summarizer's accuracy over time.
- Natural Language Processing (NLP). Utilizes NLP techniques to understand the context and semantics of the Uyghur language, improving the quality of the summaries produced.
