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http://dx.doi.org/10.9708/jksci.2020.25.09.053

Digital Signage service through Customer Behavior pattern analysis  

Shin, Min-Chan (Dept. of Computer Science, Hoseo University)
Park, Jun-Hee (Dept. of Computer Science, Hoseo University)
Lee, Ji-Hoon (Dept. of Computer Science, Hoseo University)
Moon, Nammee (Division of Computer and Information Engineering, Hoseo University)
Publication Information
Journal of the Korea Society of Computer and Information / v.25, no.9, 2020 , pp. 53-62 More about this Journal
Abstract
Product recommendation services that have been researched recently are only recommended through the customer's product purchase history. In this paper, we propose the digital signage service through customers' behavior pattern analysis that is recommending through not only purchase history, but also behavior pattern that customers take when choosing products. This service analyzes customer behavior patterns and extracts interests about products that are of practical interest. The service is learning extracted interest rate and customers' purchase history through the Wide & Deep model. Based on this learning method, the sparse vector of other products is predicted through the MF(Matrix Factorization). After derive the ranking of predicted product interest rate, this service uses the indoor signage that can interact with customers to expose the suitable advertisements. Through this proposed service, not only online, but also in an offline environment, it would be possible to grasp customers' interest information. Also, it will create a satisfactory purchasing environment by providing suitable advertisements to customers, not advertisements that advertisers randomly expose.
Keywords
Intelligent digital signage; Behavior pattern analysis; Skeleton modeling; Behavior big data; Sensor data analysis;
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Times Cited By KSCI : 2  (Citation Analysis)
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