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A review of data-driven techniques for neuromarketing

  • Baorui Li
  • , Yi Wang
  • , Kesheng Wang
  • , Dong Zhang
  • Shanghai Vocational College of Science and Technology
  • Norwegian University of Science and Technology

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

2 Citations (Scopus)

Abstract

Recent years, Fusion neuroscience and cognitive science applied in psychology, sociology, economics, management become the new research fields. Combined with the latest marketing condition, using the method of neural cognitive science to explore Subjects’ behaviour and dig out the decision-making principle of the subject’s neural activity level, and make a deep interpretation of the subject’s behavior. Then the appropriate marketing strategy was produced. In this paper, based on the latest international papers published in this field, researchers analyzed the research mechanism of neuromarketing, and reviewed the data driven technology of neuromarketing from three parts: data acquisition, preprocessing & analysis, and fusion analysis architecture. Then the advantages and disadvantages of these techniques are discussed. We expect the paper may have some reference for subsequent research.
Original languageEnglish
Title of host publicationAdvanced Manufacturing and Automation XII
EditorsYi Wang, Tao Yu, Kesheng Wang
PublisherSpringer
Pages748-755
Number of pages8
ISBN (Print)9789811993374
DOIs
Publication statusPublished - 26 Jan 2023
EventAdvanced Manufacturing and Automation XII (IWAMA 2022) - Xiamen
Duration: 1 Nov 20222 Nov 2022

Publication series

NameLecture Notes in Electrical Engineering
Volume994 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

ConferenceAdvanced Manufacturing and Automation XII (IWAMA 2022)
CityXiamen
Period1/11/222/11/22
OtherAdvanced Manufacturing and Automation XII (IWAMA 2022) (01/11/2022-02/11/2022, Xiamen)

Keywords

  • data mining
  • Neural signals
  • Data fusion
  • neuroscience
  • Neuroscience
  • Data mining

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

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