Abstract
Consumption analysis research has been so far carried out only with existing statistics and data, and it has been researched without considering real time issues. Therefore, in this study we present an analytical method which reflects both non-real-time and real-time consumption behavior by region. Consumption behavior by region is extracted with sequential pattern mining based on PrifixSpan by combining location and consumption data based on time. Also, non-real-time data (Card consumption statistics) and real-time data (SNS Data) are analyzed by examining consumption ratios of six consumption category by region. Finally, the analysis is performed by calculating the consumption figures by each region of non-real-time and real-time data in accordance with the consumption behavior ratios extracted by region. This method is meaningful as it does not only reflect regional consumption characteristics, but also reflect both non-real-time and real-time, and it is expected that we can utilize when we research various recommendation services in the future.
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Acknowledgment
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government MSIP (No. 2017008886).
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Kim, J., Moon, N. (2018). Design of Consumer Behavior Analysis by Region Through Reflecting Social Atmosphere Based on SNS. In: Park, J., Loia, V., Yi, G., Sung, Y. (eds) Advances in Computer Science and Ubiquitous Computing. CUTE CSA 2017 2017. Lecture Notes in Electrical Engineering, vol 474. Springer, Singapore. https://doi.org/10.1007/978-981-10-7605-3_163
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DOI: https://doi.org/10.1007/978-981-10-7605-3_163
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