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논문 기본 정보

자료유형
학술저널
저자정보
이기훈 (Hoseo University) 문남미 (호서대학교)
저널정보
한국정보처리학회 JIPS(Journal of Information Processing Systems) JIPS(Journal of Information Processing Systems) 제17권 제3호
발행연도
2021.1
수록면
599 - 614 (16page)

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This paper proposes a digital signage system based on an intelligent recommendation model. The proposedsystem consists of a server and an edge. The server manages the data, learns the advertisement recommendationmodel, and uses the trained advertisement recommendation model to determine the advertisements to bepromoted in real time. The advertisement recommendation model provides predictions for various products andprobabilities. The purchase index between the product and weather data was extracted and reflected usingcorrelation analysis to improve the accuracy of predicting the probability of purchasing a product. First, theuser information and product information are input to a deep neural network as a vector through an embeddingprocess. With this information, the product candidate group generation model reduces the product candidatesthat can be purchased by a certain user. The advertisement recommendation model uses a wide and deeprecommendation model to derive the recommendation list by predicting the probability of purchase for theselected products. Finally, the most suitable advertisements are selected using the predicted probability ofpurchase for all the users within the advertisement range. The proposed system does not communicate with theserver. Therefore, it determines the advertisements using a model trained at the edge. It can also be applied todigital signage that requires immediate response from several users.

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