Journal of Digital Convergence (디지털융복합연구)

The Society of Digital Policy and Management (한국디지털정책학회)
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Deep learning based image retrieval system for O2O shopping mall platform service design

O2O 쇼핑몰 플랫폼 서비스디자인을 위한 딥 러닝 기반의 이미지 검색 시스템

  • 성재경 (세종대학교 컴퓨터공학과) ;
  • 박상민 (세종대학교 컴퓨터공학과) ;
  • 신상윤 (세종대학교 컴퓨터공학과) ;
  • 김영복 (세종대학교 컴퓨터공학과) ;
  • 김용국 (세종대학교 컴퓨터공학과)
  • Received : 2017.05.23
  • Accepted : 2017.07.20
  • Published : 2017.07.28
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Abstract

This paper proposes a new service design which is deep learning-based image retrieval system for product search on O2O shopping mall platform. We have implemented deep learning technology that provides more convenient retrieval service for diverse images of many products that are sold in the internet shopping malls. In order to implement this retrieval system, real data used by shopping mall companies were used as experimental data. However, result from several experiments have confirmed deterioration of retrieval performance due to data components. In order to improve the performance, the learning data that interferes with the retrieval is revised several times, and then the values of experimental result are quantified with the verification data. Using the numerical values of these experiments, we have applied them to the new service design in this system.

본 논문은 O2O쇼핑몰 플랫폼에 있는 상품 검색을 위해 딥 러닝 기반의 이미지 검색 시스템을 이용한 서비스디자인을 제안한다. 인터넷 쇼핑몰에서 판매되는 수많은 제품에 대해서 검색 이미지를 사용하여 보다 편리한 검색 서비스가 가능한 딥 러닝(Deep Learning) 기술을 구현하였다. 본 검색 시스템 구현을 위해 현재 운영 중인 쇼핑몰 업체에서 사용하고 있는 실제 데이터를 실험데이터로 사용하였다. 그러나 본 시스템에서 여러 차례의 검색 실험을 통해서 데이터 성분으로 인한 검색 성능 저하 요인을 확인하였다. 그래서 검색 성능 향상을 위해서 검색에 방해가 되는 학습 데이터를 여러 차례 수정 정리한 후에 검증 데이터를 통해서 실험 결과 값을 수치화 하였다. 이와 같은 실험 결과의 수치 값을 활용하여 본 시스템에서 구현한 서비스디자인 설계에 반영하였다.

Keywords

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