Approaches Towards AI-Based Recommender System

Recommender Systems (RS) have application in all areas where digital information is generating at high rate. They are used to filter large volume of digital data containing user preferences, interests and behaviour patterns for products and services. Today artificial intelligence has achieved rapid development in automation, computation, knowledge-engineering, information retrieval and processing. Techniques such as fuzzy logic, neural networks, natural language processing, transfer learning, machine learning are also contributing to enhance the performance, accuracy of recommendation system and reducing problems like cold-start, data-sparsity, privacy and scalability. This paper explains the development stages and different categories of recommender system. This paper further explores the challenges and recent trends in building recommendation system.