IOT data Fusion framework for e-commerce

被引:0
|
作者
Mahesh Kulkarni P. [1 ]
Nautiyal B. [2 ]
Kumar S. [3 ]
Medidha R. [4 ]
Rameshbhai Savaliya R. [5 ]
Eknath M. [6 ]
机构
[1] Dr.Moonje Institute of Management & Computer Studies, MS, Nashik
[2] Graphic Era Deemed to be University, Visiting Faculty, Graphic Era Hill University, Uttarakhand, Dehradun
[3] Department of Computer Application, L.N Mishra Institute of Economic Development and Social Change, 1 Jawaharlal Nehru Marg, Bihar, Patna
[4] Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Andhra Pradesh, Vijayawada
[5] Head of BCA Department, Ambaba Commerce College, MIBM & DICA, SABARGAM, Gujarat, Surat
[6] Rayat Shikshan Sanstha's, S. M. Joshi College Hadapsar
来源
Measurement: Sensors | 2022年 / 24卷
关键词
And recall rate; Business logic layer; E-commerce; Marketing; Supply;
D O I
10.1016/j.measen.2022.100507
中图分类号
学科分类号
摘要
The incapacity of the present marketing data management system to evaluate and process the association between marketing data provides uncertainty regarding the qualities of the products for marketing data mining and prevents effective data management. The article advances improved trends through the exploration of forecastbusiness information from the e-commerce system.Enhance to context functionality of the e-commerce system by gathering relevant data from diverse sources.Appropriate extraction of marketing data from an e-commerce platform is achieved using distributed similarity and the information fusion approach to optimize association rules.Innovative results demonstrated the strong resilience and ability of the recommended approach to accomplish targeted marketing data mining. © 2022 The Authors
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