Scholarlink

The study explores the application of pattern mining algorithms, particularly Eclat and Parallel Eclat, in customer relationship management systems to identify frequently purchased items in supermarket transactions. Through comparative analysis, Parallel Eclat demonstrates superior computational efficiency and scalability over the classic Eclat algorithm. The findings underscore the importance of algorithmic advancements in meeting the evolving needs of customer-focused industries, offering insights for improving customer management strategies in the era of big data.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Design and Development of Efficient (Noble) Technique Using Pattern Mining Algorithms for Customer Management: A Comparison Between Eclat and Parallel Eclat Algorithm

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Vandana Paliwal,
  • Dilip Choudhary

摘要

The study explores the application of pattern mining algorithms, particularly Eclat and Parallel Eclat, in customer relationship management systems to identify frequently purchased items in supermarket transactions. Through comparative analysis, Parallel Eclat demonstrates superior computational efficiency and scalability over the classic Eclat algorithm. The findings underscore the importance of algorithmic advancements in meeting the evolving needs of customer-focused industries, offering insights for improving customer management strategies in the era of big data.