Journal of the Korea Society of Computer and Information (한국컴퓨터정보학회논문지)

Korean Society of Computer Information (한국컴퓨터정보학회)
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A WordNet-based Open Market Category Search System for Efficient Goods Registration

효율적인 상품등록을 위한 워드넷 기반의 오픈마켓 카테고리 검색 시스템

  • Hong, Myung-Duk (Dept. of Computer and Information Engineering, Inha University) ;
  • Kim, Jang-Woo (Dept. of Computer and Information Engineering, Inha University) ;
  • Jo, Geun-Sik (Dept. of Computer and Information Engineering, Inha University)
  • 홍명덕 (인하대학교 컴퓨터정보공학과) ;
  • 김장우 (인하대학교 컴퓨터정보공학과) ;
  • 조근식 (인하대학교 컴퓨터정보공학과)
  • Received : 2012.04.26
  • Accepted : 2012.07.25
  • Published : 2012.09.30
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Abstract

Open Market is one of the key factors to accelerate the profit. Usually retailers sell items in several Open Market. One of the challenges for retailers is to assign categories of items with different classification systems. In this research, we propose an item category recommendation method to support appropriate products category registration. Our recommendations are based on semantic relation between existing and any other Open Market categorization. In order to analyze correlations of categories, we use Morpheme analysis, Korean Wiki Dictionary, WordNet and Google Translation API. Our proposed method recommends a category, which is most similar to a guide word by measuring semantic similarity. The experimental results show that, our system improves the system accuracy in term of search category, and retailers can easily select the appropriate categories from our proposed method.

여러 오픈마켓에서 판매자가 동일한 상품을 등록할 시에 각 오픈마켓마다 다른 기준으로 제공되는 카테고리로 인하여 카테고리 선정에 어려움이 발생한다. 본 논문에서는 판매자가 오픈마켓에서 상품 등록 시 다른 오픈마켓에서 기 판매하고 있는 상품의 카테고리와 의미적으로 가장 연관성이 높은 카테고리를 추천하는 방법을 제안한다. 이때 입력받은 카테고리를 의미 분석하는 방법으로 형태소 분석, Wiki 낱말사전, WordNet, Google 번역 서비스를 사용하여 추출된 색인어로 카테고리를 검색한 후, 의미적 연관성 측정을 통하여 가장 의미가 비슷한 카테고리를 추천하는 방법이다. 실험 결과로 색인어 기반의 검색방법 보다 제안하는 의미분석 검색방법이 정확한 검색결과를 보여주어 시스템의 신뢰도를 향상시켰으며, 카테고리를 선택하는데 드는 시간비용을 절감해주는 것을 보인다.

Keywords

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