Impact on Social Filtering and Meta Filtering in Recommender Systems

Recommender systems are one among the most powerful tools in this digital world, usually providing explanations to their recommendations to help the web users to find their products, peoples, even their missing friends in these social communities. Until now there are various methods and approaches implemented in this recommender system. The most widely used approaches are content-based and collaborative approaches. These approaches may be studied to have the most personalized approaches and to have the best recommendations for the end users. In this paper, the filtering technique is considered as the background of every recommender system approaches. Here, the Social Filtering and Meta Filtering are presented which is mostly like to be the better recommendation in the social networking websites like facebook.com, googleplus.com, etc., as well as in the blogging websites such as blogger.com, wordpress.com, etc.