A Comprehensive Study on Recommendation Engines
Anagha N. Chaudhari, A.A. Hitham Seddig, Aliza Bt. Sarlan, Roshani Raut · 2022 6th International Conference On Computing, Communication, Control And Automation (ICCUBEA · 2022
Big Data (BD) is consistently participating in the recent computing revolution in an immense way. The volume of data generated through online platforms such as e-commerce portals comprises of huge hidden information which needs to be analyzed in-order to better serve customer's needs and retain their loyalty. Various Recommendation Engines (RE) have been proposed to tackle this problem and generate optimal recommendations based on user needs. This paper reviews and compares various types of RE highlighting their techniques, issues, applications, advantages and disadvantages. The paper also presents some results for different types of RE using sample datasets (Movie lens 100K) [12].