Text Summarization using NLTK

This Python script demonstrates text summarization using the Natural Language Toolkit (NLTK). It generates a summary of input text by selecting the top-ranked sentences based on word frequency.

Requirements

• Python 3.x
• NLTK library

Install NLTK using pip if you haven't already:

pip install nltk

Usage

1. Run the script in a Python environment.
2. You will be prompted to enter your text. Input the text you want to summarize.
3. The script will generate a summary of the input text using NLTK.

How it works

1. Input Text: The script prompts the user to input the text they want to summarize.
2. Preprocessing: The input text is tokenized into sentences using NLTK's sent_tokenize function. Each sentence is then processed to remove punctuation, stopwords, and perform stemming.
3. Word Frequency: The word frequencies in the input text are calculated using NLTK's FreqDist function.
4. Sentence Scoring: Each sentence is scored based on the sum of word frequencies of the words it contains.
5. Summary Generation: The top-ranked sentences are selected to form the summary. By default, it selects the top third of sentences with the highest scores.
6. Output: The script prints the generated summary.