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http://dx.doi.org/10.3745/JIPS.02.0157

Digital Signage System Based on Intelligent Recommendation Model in Edge Environment: The Case of Unmanned Store  

Lee, Kihoon (Dept. of Computer Science and Engineering, Hoseo University)
Moon, Nammee (Dept. of Computer Science and Engineering, Hoseo University)
Publication Information
Journal of Information Processing Systems / v.17, no.3, 2021 , pp. 599-614 More about this Journal
Abstract
This paper proposes a digital signage system based on an intelligent recommendation model. The proposed system consists of a server and an edge. The server manages the data, learns the advertisement recommendation model, and uses the trained advertisement recommendation model to determine the advertisements to be promoted in real time. The advertisement recommendation model provides predictions for various products and probabilities. The purchase index between the product and weather data was extracted and reflected using correlation analysis to improve the accuracy of predicting the probability of purchasing a product. First, the user information and product information are input to a deep neural network as a vector through an embedding process. With this information, the product candidate group generation model reduces the product candidates that can be purchased by a certain user. The advertisement recommendation model uses a wide and deep recommendation model to derive the recommendation list by predicting the probability of purchase for the selected products. Finally, the most suitable advertisements are selected using the predicted probability of purchase for all the users within the advertisement range. The proposed system does not communicate with the server. Therefore, it determines the advertisements using a model trained at the edge. It can also be applied to digital signage that requires immediate response from several users.
Keywords
Correlation Analysis; Deep Learning; Digital Signage; Edge Computing; Recommended System;
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