Beginners Guide to learn about Content Based Recommender Engines

 Broadly, there are two types of recommendation systems – Content Based & Collaborative filtering based. In this article, we’ll learn about content based recommendation system.

Recommender systems are active information filtering systems which personalize the information coming to a user based on his interests, relevance of the information etc. Recommender systems are used widely for recommending movies, articles, restaurants, places to visit, items to buy etc.

A content based recommender works with data that the user provides, either explicitly (rating) or implicitly (clicking on a link). Based on that data, a user profile is generated, which is then used to make suggestions to the user. As the user provides more inputs or takes actions on the recommendations, the engine becomes more and more accurate.

http://www.analyticsvidhya.com/blog/2015/08/beginners-guide-learn-content-based-recommender-systems/