The document describes an e-newspaper personalization system that classifies news articles and recommends personalized news to users based on their profiles. It does this in two steps:
1. It first classifies news articles from a database into categories like sports, business, etc. using a Vector Space Model classifier. Each article is represented as a word vector and assigned to the category with the most matching words.
2. It then retrieves and displays news articles to the user based on their profile preferences. The system presents a personalized newspaper containing only articles from the categories the user is interested in. This allows users to quickly access relevant news without searching through various categories.
The document evaluates the system using a 20 News