EFFICIENT RECOMMENDATION SYSTEM USING BERT TECHNOLOGY

Modelling the diverse desires of users through their economic models for recommendation systems is difficult and essential. Past Techniques utilize successive neural networks to convert the historical experiences of customers across left to right into encoded suggestion models. Recommendation systems in e-commerce are becoming an integral means of making consumers navigate the content accessible. Recommender systems are an important aspect of E-commerce platforms that assist consumers choose products of choice on a wide scale through huge investments. The metadata termed the contextual phrase, that incorporates the reference label, and the description of the quote proves have been used by several authors to locate the relevant research referenced. The lack of a well-established benchmarking dataset and no tool for recommendations that can achieve great efficiency has perhaps made the study challenging. The foundation of mutual marketplace stages in the rental property field is the personalization of recommendation systems. To support people, such a framework provides a valuable tool. The current technique aims to determine the context of the movie plot summary from the given movies using BERT as-a-service and to predict similar movie recommendations.