Precis scrapes news articles from news sites and summarizes them based on Latent Semantic Analysis.

• News articles are scraped using Python BeautifulSoup4
• Text preprocessing is done through Python NLTK where stop words and punctuations are removed and words are stemmed.
• Latent Semantic Analysis/ Indexing is carried out by first computing TF-IDF matrix from the corpus and then performing truncated SVD (Singular Value Decomposition) on the matrix. Both TF-IDF and SVD computations are done through Scikit-Learn.
• Top sentences are selected through 'Cross Method.'
• The backend uses a Flask server with MongoDB that serves a React frontend.