Recommendation System is an information filtering system created to predict products that the user may have an interest in. This technology is based on user's
past behavior as well as similar decisions made by other users. With the System you can create personalized offerings with maximal conversion for each user.
This method is based on assumption that users, that have had similar interests in the past, will prefer similar products in the future as well.
Collaborative filtering uses the data about the user’s behavior and about decisions made by other users to create personalized recommendations.
This method is based on a description of the item and a profile of the user’s preference. In other words, these algorithms recommend items that are similar to those that a user liked in the past (or is examining in the
present). Data mining technology establishes relations between products enhancing the efficiency of the Recommendation System.