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Research Proposal on Personalized Recommendation with Neural Attention Model

Research Proposal on Personalized Recommendation with Neural Attention Model

   The personalized recommendation is the highly emerging recommendation system designed to provide recommendations with customized preferences of users based on the historical data on the desired item. A personalized recommender system suggests highly relevant items and provides individualized service to the users. The personalized recommender system with a deep learning model possesses a high capacity to extract user preferences for items from a large database and improve user-s personalized recommendations. A personalized recommender system with deep learning can provide real-time customized recommendation services. The attention mechanism is the most influential concept in deep learning, which focuses on the distinctive parts of the neural network while processing a large amount of information. The attention mechanism is an additional layer in the deep learning model that sequentially processes the complex task by breaking it into smaller areas of attention. Integrating the attention model with the deep learning model in a personalized recommender system enables the system to capture both short-term and long-term user preferences. The neural attention model in personalized recommendation produces the most appropriate suggestions and improves the performance of the system.