Artificial Intelligence in Recommender Systems

Artificial intelligence is a field, which combines computer science with datasets for problem-solving. It combines machine learning and deep learning, which are frequently mentioned in conjunction with artificial intelligence. They are using AI algorithms which seek to create expert systems which make predictions or classifications based on input data. The applications for this technology are growing every day. The goal of creating intelligence has been broken down into sub-problems which consist of capabilities like Reasoning, problem-solving, Knowledge representation, Planning and decision making, Learning, Natural language processing, Perception, Social intelligence. The recommender systems used in the personalised e-services were first established twenty years ago and were developed by employing techniques and theories drawn from other artificial intelligence (AI) fields for user profiling and preference discovery. The past few years have seen a huge increase in successful AI-driven applications. In this paper we covered applications of AI, components of AI, AI process with advantages and disadvantages of AI. along with this we covered how ML based recommender system work. This may help in understanding basics of AI and will lead better research in the field of AI and its use in and recommender systems.