零售场景中基于MapReduce框架的深度学习分类序列关联规则挖掘

IF 1.1 4区计算机科学 Q3 COMPUTER SCIENCE, CYBERNETICS

Cybernetics and Systems Pub Date : 2023-02-27 DOI:10.1080/01969722.2023.2166256

K. Matrouk, J. Nalavade, Saeed Alhasen, Meena Chavan, Neha Verma

引用次数: 0

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

MapReduce Framework Based Sequential Association Rule Mining with Deep Learning Enabled Classification in Retail Scenario

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Cybernetics and Systems 工程技术-计算机：控制论

CiteScore

4.30

自引率

5.90%

发文量

审稿时长

>12 weeks

期刊介绍： Cybernetics and Systems aims to share the latest developments in cybernetics and systems to a global audience of academics working or interested in these areas. We bring together scientists from diverse disciplines and update them in important cybernetic and systems methods, while drawing attention to novel useful applications of these methods to problems from all areas of research, in the humanities, in the sciences and the technical disciplines. Showing a direct or likely benefit of the result(s) of the paper to humankind is welcome but not a prerequisite. We welcome original research that: -Improves methods of cybernetics, systems theory and systems research- Improves methods in complexity research- Shows novel useful applications of cybernetics and/or systems methods to problems in one or more areas in the humanities- Shows novel useful applications of cybernetics and/or systems methods to problems in one or more scientific disciplines- Shows novel useful applications of cybernetics and/or systems methods to technical problems- Shows novel applications in the arts