Abstract

The Recommendation System is one of the latest application tools developed through Deep Learning research activities under the Machine Learning technical domain. The application might have recognized an idea for establishing a user-item relationship on consumables with guidance from the user’s historical purchasing transaction data to achieve future demand predictions. Researchers had been able to bring out memory-based concepts at the beginning supplemented with model-based tools for further refinements with time. Incidentally, the significance of RS was well accepted by business entities, hence personalized services had been initiated to reduce user agony to search out the desired item. In recent years marked improvement was observed with the development of hybrid RS ornamented with the addition of Transformers in the model. The success of the introduction of Next Basket Recommendation relied on the capacity to analyze the user sequential change pattern in purchasing behavior.