Publications

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Papers

Travel index forecasting using credit card transaction

Date of publication
2021.01.01
Issuing agency (Year)
KDISS(2021)
Author
Lee Hye ree, Kang suk woo, Kim min hee
Link
http://www.kdiss.org/

Abstract

Credit card data is one of the most important data that reflects the lives of customers. Effective marketing requires understanding the customer's life, so in this paper we build a predictive model that predicts the customer's life through credit card transaction data. In particular, focus on how to predict customers who are likely to leave 'overseas travel' during various life events. There are many existing predictive model methodologies, but this study presents the FastText methodology, which is applied primarily to text data, and the newly proposed adaptive sum of term scoring (AWST score).