Precise Marketing of E-Commerce Products Based on KNN Algorithm.


Journal

Computational intelligence and neuroscience
ISSN: 1687-5273
Titre abrégé: Comput Intell Neurosci
Pays: United States
ID NLM: 101279357

Informations de publication

Date de publication:
2022
Historique:
received: 19 04 2022
revised: 18 06 2022
accepted: 29 06 2022
entrez: 22 8 2022
pubmed: 23 8 2022
medline: 24 8 2022
Statut: epublish

Résumé

In order to better understand the purchase decision-making process of consumers, this paper makes an in-depth study on the precision marketing of e-commerce products on the basis of KNN algorithm. Through data mining, classic KNN algorithm, BPNN algorithm, and other methods, this paper takes the price and purchase intention of e-commerce agricultural products as an example. Based on the classic nearest neighbor algorithm, binomial function is combined with Euclidean distance formula when calculating the nearest neighbor through similarity. The particle swarm optimization algorithm is used to optimize the binomial function coefficient and the

Identifiants

pubmed: 35990135
doi: 10.1155/2022/4966439
pmc: PMC9388237
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

4966439

Informations de copyright

Copyright © 2022 Jianfeng Zou and Hui Li.

Déclaration de conflit d'intérêts

The authors declare no potential conflicts of interest.

Références

Sensors (Basel). 2020 Jan 18;20(2):
pubmed: 31963628
J Healthc Eng. 2021 Jan 28;2021:8811837
pubmed: 33575022
J Healthc Eng. 2021 Mar 4;2021:6678526
pubmed: 33747420
RSC Adv. 2021 Jul 27;11(42):26008-26015
pubmed: 35479454
Comput Intell Neurosci. 2022 Mar 19;2022:9501246
pubmed: 35345796
J Healthc Eng. 2021 Apr 3;2021:5574152
pubmed: 33884158

Auteurs

Jianfeng Zou (J)

Guangzhou College of Technology and Business, Guangzhou, China.

Hui Li (H)

Guangzhou College of Technology and Business, Guangzhou, China.

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