Clustering Analysis for Shoppers’Trajectory in Store Using String Similarity

• 발행기관: 한국IT서비스학회
• 저자명: M. Alex Syaekhoni Young S. Kwon
• 간행물 정보: 『한국IT서비스학회 학술대회 논문집』2015추계학술대회, 486~492쪽, 전체 7쪽
• 주제분류: 공학 > 전자/정보통신공학
• 파일형태: PDF
• 발행일자: 2015.11.30

영문 초록

The huge collection of movement data is significant and precious information in various application domains. Many different studies have been done towards interpreting this data to get some hidden information on it. For this purpose, grouping certain shoppers based on their behaviors is one of important strategies in grocery store business. Shoppers’trajectory presents how the behavior of shoppers is. For the marketing side, shoppers movement trajectories are valuable to be analyzed in order to have better understanding of their behaviors in a store. To have proper and meaningful groups of shopper, business intelligence strategy based on clustering and string similarity analysis is performed. And in the experimental results this approach has performed better than traditional approach. Then hopefully, this valuable information will help store managers to manage store and leads to increase sales accordingly.

목차

1. Introduction

2. Related research

3. Proposed Approach

4. Experiment Result and Discussion

[References]

키워드

clustering trajectory string similarity