Precise Marketing Data Mining Method of E-Commerce Platform Based on Association Rules

Hong-ni Zhang, Ashutosh Dhar Dwivedi*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

4 Citations (Scopus)


The current marketing data management method cannot analyze and mine the correlation between marketing data, which leads to the confusion of the attributes of marketing data mining results and the inability to realize efficient data scheduling. This paper introduces improved association rules into precision marketing data mining of e-commerce platform. Optimize the background hardware of the e-commerce platform, collect and analyze the multi-source data. Information fusion method is used to optimize association rules, and combined with distributed similarity, accurate mining of marketing data of e-commerce platform is completed. Experimental results show that the proposed method can realize precision marketing data mining and has high robustness.

Original languageEnglish
JournalMobile Networks and Applications
Issue number6
Pages (from-to)2400-2408
Number of pages9
Publication statusPublished - 5 Feb 2023
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.


  • Association rules
  • Data mining
  • E-commerce platform
  • Precision marketing


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