Due to COVID-19, changes in consumption trends are taking place in the distribution sector, such as an increase in non-face-to-face consumption and a rapid growth in the online shopping market. However, it is difficult for small and medium-sized export sellers to obtain forecast information on the export market by country, compared to large distributors who can easily build a global sales network. This study is about the prediction of export amount and export volume by country and item for market information analysis of small and medium export sellers. A prediction model was developed using Lasso, XGBoost, and MLP models based on supervised learning and deep learning, and export trends for clothing, cosmetics, and household electronic devices were predicted for Korea's major export countries, the United States, China, and Vietnam. As a result of the prediction, the performance of MAE and RMSE for the Lasso model was excellent, and based on the development results, a market analysis system for small and medium sellers was developed.

1. 서 론
2. 기존연구
3. 데이터 전처리 및 예측모델
    3.1 활용 데이터
    3.2 데이터 전처리
    3.3 예측모델
4. 결과 분석
    4.1 분석 결과
5. 활용 및 추후연구
    5.1 연구 결과의 활용 및 기대효과
    5.2 향후 연구 방향
Acknowledgement
References

• Dong-Gil Na(Electronics and Telecommunications Research Institute) | 나동길 (한국전자통신연구원) Corresponding author
• Yeong-Woong Yu(Electronics and Telecommunications Research Institute) | 유영웅 (한국전자통신연구원)