/NLP-Text-Summarization

text Summarization: Abstractive, Extractive, and Transformer-based approaches. This project explores various text summarization techniques, including both abstractive and extractive approaches, using traditional methods (`NLTK`, and `spaCy`, `Gensim`, and `Sumy`) as well as advanced Large Language Models (LLMs).

Primary LanguageJupyter Notebook

NLP Text Summarization

Text summarization refers to the technique of shortening long pieces of text, with the intention of creating a coherent and fluent summary having only the main points outlined in the document. Basically, the process of creating shorter text without removing the semantic structure of text.