Abstract:
Recommendation systems play a very important part in filtering personalized information, relevant to users. Recommendation is used in almost every social networking, e-learning and e-commerce systems, these days. However, there are different types of recommendation techniques and we have discussed about few techniques and their advantages and limitations. Each technique is implemented for different type of system and each technique is evaluated using some common evaluation metrics. In this paper, we have discussed brief depictions of recommender systems, in general, and summarise various state-of-the-art metrics. We have explained some real life examples for recommender system implemented. We have discuss some limitations faced by current recommender systems also we have categorized recommender systems according to our understanding and it will help for future research directions. The main purpose of this paper is to study concepts behind current recommender system, discuss about the existing limitations of recommender systems and present the steps involving in recommendation in a precise manner.
Page(s):
503-511
DOI:
DOI not available
Published:
Journal: Science International, Volume: 24, Issue: 4, Year: 2012