Journal of the Korea Convergence Society (한국융합학회논문지)

Korea Convergence Society (한국융합학회)
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A Study on the Development of Product Planning Prediction Model Using Logistic Regression Algorithm

로지스틱 회귀 알고리즘을 활용한 상품 기획 예측 모형 개발에 관한 연구

  • Ahn, Yeong-Hwil (Division of Computer Engineering, Kongju National University) ;
  • Park, Koo-Rack (Division of Computer Science & Engineering, Kongju National University) ;
  • Kim, Dong-Hyun (Dept. of IT Artificial Intelligence, Korea Nazarene University) ;
  • Kim, Do-Yeon (Division of Computer Engineering, Kongju National University)
  • 안영휘 (공주대학교 대학원) ;
  • 박구락 (공주대학교 컴퓨터공학부) ;
  • 김동현 (나사렛대학교 IT인공지능학부) ;
  • 김도연 (공주대학교 대학원)
  • Received : 2021.08.31
  • Accepted : 2021.09.20
  • Published : 2021.09.28
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Abstract

This study was conducted to propose a product planning prediction model using logistic regression algorithm to predict seasonal factors and rapidly changing product trends. First, we collected unstructured data of consumers in portal sites and online markets using web crawling, and analyzed meaningful information about products through preprocessing for transformation of standardized data. The datasets of 11,200 were analyzed by Logistic Regression to analyze consumer satisfaction, frequency analysis, and advantages and disadvantages of products. The result of analysis showed that the satisfaction of consumers was 92% and the defective issues of products were confirmed through frequency analysis. The results of analysis on the use satisfaction, system efficiency, and system effectiveness items of the developed product planning prediction program showed that the satisfaction was high. Defective issues are very meaningful data in that they provide information necessary for quickly recognizing the current problem of products and establishing improvement strategies.

본 연구에서는 계절적인 요인과 급변하는 상품의 트렌드를 사전예측하기 위해 로지스틱 회귀 알고리즘을 이용한 상품기획 예측 모형을 제안하고자 수행되었다. 먼저 웹크롤링을 이용하여 포털 사이트 및 온라인 마켓의 소비자의 비정형 데이터를 수집하고 정형 데이터 변환을 위한 전처리 작업을 통해 상품에 대한 의미 있는 정보를 분석하였다. 최종 수집된 11,200개의 데이터셋은 Logistic Regression을 이용하여 상품에 대한 소비자의 만족도, 빈도분석, 상품에 대한 장점과 단점을 분석할 수 있었다. 분석 결과 소비자의 만족도는 92%이었으며, 빈도분석을 통해 상품에 대한 불량이슈를 확인할 수 있었다. 또한, 개발된 상품 기획 예측 프로그램에 대한 사용 만족도, 시스템 효율성, 시스템 효과성 항목에 대한 분석결과에서도 만족도가 높게 나타났다. 특히, 불량이슈는 상품에 대한 현 문제를 신속히 인지하고 개선 전략을 수립하는데 필요한 정보를 제공한다는 점에서 매우 의미 있는 자료가 된다.

Keywords

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