Recommender Engine – Under The Hood
Many of us are bombarded with various recommendations in our day to day life, be it on e-commerce sites or social media sites. Some of the recommendations look relevant but some create range of emotions in people, varying from confusion to anger.
There are basically two types of recommender systems, Content based and Collaborative filtering. Both have their pros and cons depending upon the context in which you want to use them.
Content based: In content based recommender systems, keywords or properties of the items are taken into consideration while recommending an item to an user. So, in a nutshell it is like recommending similar items. Imagine you are reading a book on data visualization and want to look for other books on the same topic. In this scenario, content based recommender system would be apt.
Collaborative Filtering: Well to drive home the point, the below picture is the best example. Customer A has bought books x,y,z and customer B has bought books y,z. Now collaborative filtering technique would recommend book x to customer B. This is both the