Abstract

Internet is the easiest and cheapest way to do business nowadays. Due to this every organization moves toward it. This increases a variety of problems like information overload, irrelevant information that creates confusion overhead to the customer as well as to the enterprise. Recommendation systems in online business play a vital role in assisting the customers to find the best and relevant products that meet their requirements. It is widely used in the online business environment because of its powerful personalization and efficiency features, hence variety of its design techniques are the attention of the researchers. This paper discusses various recommendation models based on users’ reviews and ratings of the products. It proposes knowledge-based recommendation system that uses heterogeneous information source in the form of triplet relation between user and the product. The proposed system compares with the baselines of the other recommendation systems also.

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