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基于过程挖掘的路径分析:以购物中心为例。

Analyzing of Gender Behaviors from Paths Using Process Mining: A Shopping Mall Application.

机构信息

Department of Industrial Engineering, Istanbul Technical University, Istanbul 34367, Turkey.

Instituto Universitario de Investigación de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València, Camino de Vera S/N, 46022 Valencia, Spain.

出版信息

Sensors (Basel). 2019 Jan 29;19(3):557. doi: 10.3390/s19030557.

Abstract

The study presents some results of customer paths' analysis in a shopping mall. Bluetooth-based technology is used to collect data. The event log containing spatiotemporal information is analyzed with process mining. Process mining is a technique that enables one to see the whole process contrary to data-centric methods. The use of process mining can provide a readily-understandable view of the customer paths. We installed iBeacon devices, a Bluetooth-based positioning system, in the shopping mall. During December 2017 and January and February 2018, close to 8000 customer data were captured. We aim to investigate customer behaviors regarding gender by using their paths. We can determine the gender of customers if they go to the men's bathroom or women's bathroom. Since the study has a comprehensive scope, we focused on male and female customers' behaviors. This study shows that male and female customers have different behaviors. Their duration and paths, in general, are not similar. In addition, the study shows that the process mining technique is a viable way to analyze customer behavior using Bluetooth-based technology.

摘要

本研究展示了购物中心顾客路径分析的一些结果。研究使用基于蓝牙的技术来收集数据。使用流程挖掘技术对包含时空信息的事件日志进行分析。与以数据为中心的方法不同,流程挖掘技术可以让人们看到整个流程。我们在购物中心安装了 iBeacon 设备,这是一种基于蓝牙的定位系统。在 2017 年 12 月以及 2018 年 1 月和 2 月期间,我们捕获了近 8000 名顾客的数据。我们旨在通过顾客的路径来研究其性别行为。如果顾客去男洗手间或女洗手间,我们就能确定他们的性别。由于研究范围广泛,我们专注于男顾客和女顾客的行为。本研究表明,男顾客和女顾客的行为存在差异。他们的停留时间和路径总体上并不相似。此外,研究还表明,使用基于蓝牙的技术和流程挖掘技术是分析顾客行为的一种可行方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df3f/6387088/a05e67bcee0c/sensors-19-00557-g001.jpg

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