Overview / Usage

A comprehensive algorithm that generates a brief summary of a given research paper.Paper summarization is a crucial tool that helps researchers, students, and professionals save time and effort when working with research papers. However, summarizing research papers can be a daunting task, especially when the papers are lengthy and complex. This is where the Paper Summarizer comes in. It is a Python-based tool that automatically summarizes research papers by extracting the most important sentences from the text. The tool is based on natural language processing techniques and uses machine learning algorithms to identify key phrases and sentences that provide the most significant insights.

Methodology / Approach

Features

The Research Paper Summarizer has several features that make it an efficient and effective tool for summarizing research papers. These features include:

Sentence Extraction The tool uses a machine learning algorithm to identify and extract the most important sentences from the research paper. The algorithm takes into account several factors such as sentence length, frequency of occurrence, and relevance to the research topic to determine the most important sentences.

Customizable Summary Length The tool allows users to specify the desired length of the summary. Users can specify the number of sentences or the percentage of the original text they want to be included in the summary.

Automatic Keyword Extraction The tool automatically extracts the most important keywords from the research paper. This helps users to get a quick overview of the main topics covered in the paper.

Command-Line Interface The tool has a command-line interface that makes it easy to use. Users can run the tool from the command line by providing the path to the research paper they want to summarize.

Repository

https://github.com/abish003/Paper-Summerizer.git

Collaborators