Added Text Summarization Model.

[akshaydubey05]

ISSUE:- #586

This text summarization model uses the Natural Language Toolkit (NLTK) library for text processing and Networkx for implementing TextRank. Features:

• Automatic Summarization: The algorithm automatically generates summaries for input text by identifying important sentences using graph-based ranking techniques.

• Customizable: Users can adjust parameters such as the similarity threshold to control the length and quality of the summary.

• Natural Language Processing: The project utilizes natural language processing techniques such as tokenization, stop word removal, and cosine similarity computation.

• Python Implementation: Implemented in Python using libraries such as NLTK, NumPy, and NetworkX.

[akshaydubey05]

Hi, I have created a new pull request. In this case, there is no Python file or log file.

(Actually, i am a beginner in this and therefore previous one got messed up.)

[invigorzz313]

No worries. You could have just committed the changes in the previous PR too without deleting it.

And here I notice some errors while generating the summary to the text, what is your take on it?

[Niketkumardheeryan]

HI @akshaydubey05 , good work but try to write code in separate cells for better readability and before using data analyze it because data is everything when you work in this field.

[akshaydubey05]

Thanks for the review ,i will make changes accordingly.

[akshaydubey05]

• Hi, @Niketkumardheeryan As per your requirements, I have made different blocks in the.ipynb file.