Recommendation Systems in the Big Data Era

Rapid progression in technology and increasinguse of social media platforms like Facebook, Instagram andTwitter has altered the way of articulating people’s judgment,observation and sentiments about specific product, services,and more. This leads to the production and accumulation ofmassive amount of data. Recommendation systems are gettingimpetus when it comes to find insights from this data to makedecisions that can be represented in various statistical andgraphical forms. They have proven useful in predicting orrecommending products ranging from food, movies,restaurants etc. This paper presents an overview aboutrecommendation systems and a review of generation ofrecommendation methods based on categories like contentbased, collaborative, and hybrid approaches. The paper willenlist the limitations which the present recommendationsystem faces and the possible improvements required in theircapabilities to fit into a wider range of application areas.