Introduction
Automatic text summarization, or just text summarization, is the process of creating a short and coherent version of a longer document.
It can be achieved using NLP(natural language processing).
There are two main types of text summarization using NLP:
1)Extraction-based summarization.
2)Abstraction-based summarization.
Abstract
• “Data” in today’s world is akin to “oil”.
• To read and decipher huge chunks of data is not a very easy task.
• Short summary of anything is easy to manage and decipher.
• Thus, our project Automatic Text Summarizer will summarize these humongous pieces of data in order to give a short summary.
• This will make the time-consuming process of reading and understanding the data into a short, automatic and manageable time-conserving process.
Functions
• Paragraph Summarizer.
• File Summarizer.
• URL Summarizer.
• Comparison between different models of summarizer.
• Multiple File Summarizer.
Requirements
Software :- Python 3.6 or later.
Modules/Libraries Used: Nltk Spacy Gensim Tkinter (GUI)