IE interfaces (산업공학)

Korean Institute of Industrial Engineers (대한산업공학회)
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A New Approach to Spatial Pattern Clustering based on Longest Common Subsequence with application to a Grocery

공간적 패턴클러스터링을 위한 새로운 접근방법의 제안 : 슈퍼마켓고객의 동선분석

  • Jung, In-Chul (Department of Industrial and Systems Engineering, Dongguk University) ;
  • Kwon, Young-S. (Department of Industrial and Systems Engineering, Dongguk University)
  • 정인철 (동국대학교 산업시스템공학과) ;
  • 권영식 (동국대학교 산업시스템공학과)
  • Received : 2011.07.11
  • Accepted : 2011.10.31
  • Published : 2011.12.01
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Abstract

Identifying the major moving patterns of shoppers' movements in the selling floor has been a longstanding issue in the retailing industry. With the advent of RFID technology, it has been easier to collect the moving data for a individual shopper's movement. Most of the previous studies used the traditional clustering technique to identify the major moving pattern of customers. However, in using clustering technique, due to the spatial constraint (aisle layout or other physical obstructions in the store), standard clustering methods are not feasible for moving data like shopping path should be adjusted for the analysis in advance, which is time-consuming and causes data distortion. To alleviate this problems, we propose a new approach to spatial pattern clustering based on longest common subsequence (LCSS). Experimental results using the real data obtained from a grocery in Seoul show that the proposed method performs well in finding the hot spot and dead spot as well as in finding the major path patterns of customer movements.

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References

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