Text Summarization with NLTK in Python
Use Jupiter notebook, label question, code and screenshot
Natural Language Processing (NLP) has a subfield called text summarization that works with extracting summaries from massive amounts of text. NLP-based approaches and deep learning-based techniques are the two primary categories of text summarizing techniques. This article will demonstrate a straightforward NLP-based text summarizing method. In this essay, we won't employ any machine learning li
aries. Instead, we will only utilize the NLTK li
ary in Python to summarize Wikipedia articles.
Getting Wikipedia Articles We first need to fetch Wikipedia articles from the internet before we can summarize them. We'll make use of a few li
aries to accomplish this. The first li
ary that has to be downloaded is the excellent Python web scraping tool called delicious soup.
https:
ealpython.com
eautiful-soup-web-scraper-python
Execute the following command at the command prompt to download the Beautiful Soup utility.
pip install beautifulsoup4
pip install lxml
The most popular platform for creating Python programs that use human language data is called NLTK. Along with a collection of text processing li
aries for categorization, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial-strength NLP li
aries, and an active discussion forum, it offers simple interfaces to more than 50 corpora and lexical resources, including WordNet.
pip install nltk
You should implement the following:
· Preprocessing
· Removing Square Brackets and Extra Spaces
· Removing special characters and digits
· Converting Text To Sentences
· Find Weighted Frequency of Occu
ence
· Calculating Sentence Scores
· Getting the Summary
Welcome to added more info in
Now, we have a dictionary called sentence scores that lists sentences along with their related scores. We can use the top N sentences that received the greatest scores to summarize the article. Your script should prints the top seven sentences from the database. And print some data graph
Your submission should include the Jupyter notebook scripts and a screenshot for the outputs.