aryankhokhar1/text-summarization-by-python

"Python-based Text Summarization using TextRank. Automates condensing of text. Customizable and scalable. Simplify content curation."

Text-Summarization-By-Python

"Python-based Text Summarization using TextRank. Automates condensing of text. Customizable and scalable. Simplify content curation."

This project presents an implementation of text summarization using Python and the TextRank algorithm. Text summarization is a crucial task in natural language processing (NLP) that involves condensing large amounts of text into shorter, coherent summaries while retaining key information. Leveraging the TextRank algorithm, which is based on the PageRank algorithm used by Google for ranking web pages, this project offers a simple yet effective solution for automatically generating summaries from textual content.

The TextRank algorithm works by representing text as a graph, where sentences are nodes and relationships between sentences are represented by edges. It then assigns importance scores to each sentence based on the graph structure and iteratively updates these scores until convergence. The sentences with the highest scores are selected to form the summary.

Key features of this project include:

TextRank Algorithm: The TextRank algorithm serves as the backbone for summarization, allowing the identification of crucial sentences and phrases within the input text.

Summarization: The system generates concise summaries by extracting the most relevant sentences from the input text, providing users with a condensed version of the original content.

Customizability: Users can easily adjust parameters and settings to control the length and quality of the generated summaries, tailoring the summarization process to their specific needs.

Pythonic Implementation: Implemented in Python, the project is easily accessible and can be seamlessly integrated into existing Python projects or workflows.

Scalability: The solution is designed to efficiently process large volumes of text data, making it suitable for applications requiring summarization of extensive textual content.

To use the system, users need Python 3.x installed along with the TextRank library. The summarization process involves initializing the TextRank summarizer, passing the input text to the summarizer, and obtaining the generated summary as output.

Contributions to the project are welcome. Users can contribute by submitting issues, feature requests, or pull requests to help enhance the functionality and usability of the system.

This project is licensed under the MIT License, granting users the freedom to use, modify, and distribute the code for both commercial and non-commercial purposes.