To deal with information overloaded problem on the internet, there is need to filter, efficient and accurately deliver the pertinent information. So, recommendation system is used to resolve this problem. Recommendation system filters out the information fragment according to user behaviour or interest. Recommendation system can predict the interest of the user and also predict that the user would prefer any particular item or not. For both users and service providers, recommendation system is profitable and it is also effective in increasing sales of many products. This paper explores many recommendation techniques and compares their characteristics, strength and weaknesses to enhance the execution of the recommendation system.
Paper
Full text
RECOMMENDATION SYSTEMS: A REVIEW REPORT
Semantic Scholar · Computer Science · 2017
Abstract
To deal with information overloaded problem on the internet, there is need to filter, efficient and accurately deliver the pertinent information. So, recommendation system is used to resolve this problem. Recommendation system filters out the information fragment according to user behaviour or interest. Recommendation system can predict the interest of the user and also predict that the user would prefer any particular item or not. For both users and service providers, recommendation system is profitable and it is also effective in increasing sales of many products. This paper explores many recommendation techniques and compares their characteristics, strength and weaknesses to enhance the execution of the recommendation system.