An anticipation model of potential customers’ purchasing behavior based on clustering analysis and association rules analysis

Author:

Chang Horng-Jinh,Hung Lun-Ping,Ho Chia-Ling

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference29 articles.

1. Abidi, S. S., & Ong, J. (2000). A data mining strategy for inductive data clustering: A synergy between self-organizing neural networks and K-means clustering techniques. In Proceedings of IEEE TENCON (pp. 568–573). Kuala Lumpur.

2. Agrawal, R., & Srikant, R. (1994). Fast algorithms for mining association rules in large databases. In Proceedings of the 20th international conference on very large databases (pp. 487–499). Santiago, Chile.

3. A personalized recommender system based on web usage mining and decision tree;Cho;Expert Systems with Applications,2002

4. Clustering web transactions using rough approximation;De;Fuzzy Sets and Systems,2004

5. Han, J., & Fu, Y. (1995). Discovery of multiple-level association rules from large database. In The twenty-first international conference on very large data bases (pp. 420–431). Zurich, Switzerland.

Cited by 33 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Unveiling Purchasing Patterns in Grocery Store Consumer Segmentation Insight From K - Means Clustering;2023 1st IEEE International Conference on Smart Technology (ICE-SMARTec);2023-07-17

2. Design and Purchase Intention Analysis of Cultural and Creative Goods Based on Deep Learning Neural Networks;Computational Intelligence and Neuroscience;2022-08-29

3. Application of Apriori Algorithm for CRM Improvement - Case Study from Montenegro;2022 8th International Conference on Computer Technology Applications;2022-05-12

4. A Comparative Review of Expert Systems, Recommender Systems, and Explainable AI;2022 IEEE 7th International conference for Convergence in Technology (I2CT);2022-04-07

5. A Management Technology of Electrical User Data Label Based on Artificial Intelligence Identification;2022 IEEE 2nd International Conference on Power, Electronics and Computer Applications (ICPECA);2022-01-21

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3