Soft-computing based recommendation system: A comparative study

Abstract

In modern days, recommendation system has left a huge impact on the society. It gives personalized list of items or services to its users in a shorter time. When there is a huge number of information, then it needs to be filtered to generate relevant recommendation. There are different filtering techniques used in recommendation system. To optimize its performance some soft computing techniques can also be added along with those filtering techniques. This article gives an overview of evaluation metrics, phases, challenges and how soft computing techniques are merged along with the filtering techniques. This paper also presents some statistical analysis of popularity of various filtering techniques and soft computing techniques used in recommendation system.