A membrane computing approach to classify Macao visitor expenditure profile

  • Jinxing Hao
  • , Wei Sun*
  • , Minhas Mahsud
  • , Rui Hong Sun
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Membrane computing also called P system, seeks to discover new computational models from the study of cellular membranes. In this study, we reported our initial efforts to classify Macao visitor expenditure profile using a membrane computing approach. Specifically, we designed a novel P system including specific membrane structure and membrane rules to realize an improved k-medoids clustering algorithm. We also empirically evaluated the new P system with a dataset from a large-scale visitor profile survey supported by Macao Government Tourist Office. Results reveal that the new P system is more robust to initial centers and achieves higher clustering accuracy as compared to the classical k-medoids clustering and the classical k-means method. In addition, we analyzed the demographic and behavior profile of the extracted six expenditure clusters and discussed the theoretical and practical implications of this study.

Original languageEnglish
Title of host publication14th International Conference on Services Systems and Services Management, ICSSSM 2017 - Proceedings
EditorsXiaoqiang Cai, Jiafu Tang, Jian Chen
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509063697
DOIs
StatePublished - 28 Jul 2017
Event14th International Conference on Services Systems and Services Management, ICSSSM 2017 - Dalian, China
Duration: 16 Jun 201718 Jun 2017

Publication series

Name14th International Conference on Services Systems and Services Management, ICSSSM 2017 - Proceedings

Conference

Conference14th International Conference on Services Systems and Services Management, ICSSSM 2017
Country/TerritoryChina
CityDalian
Period16/06/1718/06/17

Keywords

  • Expenditure analysis
  • Improved k-medoids algorithm
  • Marketing strategy
  • Membrane computing
  • Visitor profiling

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