The document discusses an intelligent news portal that uses clustering and classification techniques to autonomously process large volumes of news from various sources and present the most important stories to users. It clusters similar news stories together and classifies the clusters into predefined categories. The proposed system collects news feeds, represents the stories as vectors, clusters them using hierarchical agglomerative clustering, and classifies the clusters using a k-nearest neighbors classifier. The system aims to reduce redundancy and determine importance automatically without human intervention.