Automatic text summarization is the task of producing a concise and fluent summary while preserving key information content and overall meaning. There are broadly two different approaches that are used for text summarization: Extractive Summarization and Abstractive Summarization.
Extractive summarization extracts the most important and meaningful sentences from the text document and forms a summary. Here, a simple text summarizer is built to summarise Wikipedia articles using the extractive method. The top N sentences with the highest scores are extracted for summary generation with the help of Python NLTK library. To fetch the Wikipedia articles from the web, BeautifulSoup library is used.