In today's information era, people are keen to know about various topics & events but are unable to keep up because of lack of time & information overload. Inspired by the need to say “Let me know”, `LeMeNo' aims to be an application that provides personalized news & event updates to its users without losing out on time or having to go through irrelevant content. This paper presents the event-based approach used by LeMeNo for News Recommendation based on user interest. The Recommendation System is based on both news & users interests. News articles are recommended based on machine learning techniques like clustering of similar articles, predicting their category, content similarity & keyword extraction. The system learns user interests based on time spent on reading an article, whether user likes/dislikes the article as well as user specified levels of interest in various topics. The proposed system provides a unique Event Timeline feature, which filters out multiple news articles related to an event, displays them in chronological order & appends new upcoming related articles, thus providing a journey of that event.