Abstract: Nowadays, implemented different software applications, increasing user engagement. Social influence plays an important role in product marketing. Our Social Media creates an online user group and shares their experiences, interests and views with each other. To provide better service to users and grow a business, there is a need to analyze user interest, need, preferences, and habits. The social circle and influence of people in contact also matters to the user's purchase. Sequential actions of friends and temporal autocorrelation influences user point of interest. Design and development of proposed work includes recommendation generation based on deep learning. Recommender systems which can utilize information in social media, newspaper, TVs, internet, including user preferences, item's general acceptance, and influence from social friends. This paper includes the study of various sequential modelling techniques. Based on the study of existing system, a new system is proposed for sequential modelling.
Keywords: Recommender Systems, Social Media, Machine Learning.
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DOI:
10.17148/IJARCCE.2021.106128
