Big data analytics-recommendation system with Hadoop Framework

Big data is a term for massive data sets having large, more varied and complex structure with the difficulties of storing, analyzing and visualizing for further processes or results. Recommendation system provides the facility to understand a person's taste and find new, desirable content for them automatically based on the pattern between their likes and rating of different items. Although people's tastes vary, they do follow patterns. People tend to like things that are similar to other things they like as well as other similar behavioral person likes. Sometimes these types of patterns can be related with the relevancy of items. On the other hand, we could figure out what items are similar to what we already liked, again by looking to others apparent preferences. The movie recommendation system is proposed for large amount data available on the web in the form of ratings, reviews, opinions, complain, remarks, feedback, and comments about any item (product, event, individual and services) using Hadoop Framework. Depending on the taste of the person a list of movies would be recommended to him.