DEEP LEARNING BASED SOCIAL MEDIA RECOMMENDATION SYSTEM
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Date
2022
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Publisher
UMT, Lahore
Abstract
In past few decades, with the advent of online social networking sites, the field of personalized proposals that take use of the feature of social interactions has emerged as a particularly intriguing issue for researchers to investigate. This trend is expected to continue in the foreseeable future. The classification and suggestion system that is deployed for the purpose of determining the interests of users of social networking sites (SNS) is an important component in a variety of different businesses, particularly advertising. Advertising that is personalized helps firms stand out from the sea of generic internet ads while simultaneously increasing their relevancy to customers and eliciting favorable reaction from those clients. Whereas the vast majority of studies on user interest classification have concentrated on textual data, in this experiment I utilizes the user-generated image posts the model will precisely anticipate the user’s interest. As a consequence, this study categorizes the interests of social networking service users by employing graphics An artificial neural network (ANN) was used to characterize the interests of consumers, and for our user interest classification system, a variety of convolutional neural network (CNN)-based models were evaluated. In this study, neural network (NN) model made use of CNN-based classification models in order to categories photographs taken from users' social networking posts.