2022
DOI: 10.4018/jcit.302244
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E-Commerce Precision Marketing and Consumer Behavior Models Based on IoT Clustering Algorithm

Abstract: This article aims to study e-commerce precision models and consumer behavior models based on clustering algorithms, and at the same time conduct detailed research on the Gaussian mixture distribution algorithm, consumer behavior and model construction, and precision marketing strategies in the clustering algorithm. First, a lot of analysis and demonstration of precision marketing strategies and the construction of consumer behavior models are carried out, and then the clustering algorithm-based electronic some… Show more

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Cited by 9 publications
(2 citation statements)
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References 27 publications
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“…McKelvey et al, 2005), Gaussian distribution is still a useful first approximation in modelling that facilitates researchers and practitioners to advance their studies (e.g. Maliani et al, 2012;Wen and Liu, 2013;Guo and Zhai, 2022). Approximately 99.7% of the random values in Gaussian distribution fluctuate up to 3 standard deviations from the centre of the distribution, so it is not highly likely to draw some extreme values from either left or right tails of Gaussian distribution.…”
Section: Probability Distribution For Financial Distress Outlookmentioning
confidence: 99%
“…McKelvey et al, 2005), Gaussian distribution is still a useful first approximation in modelling that facilitates researchers and practitioners to advance their studies (e.g. Maliani et al, 2012;Wen and Liu, 2013;Guo and Zhai, 2022). Approximately 99.7% of the random values in Gaussian distribution fluctuate up to 3 standard deviations from the centre of the distribution, so it is not highly likely to draw some extreme values from either left or right tails of Gaussian distribution.…”
Section: Probability Distribution For Financial Distress Outlookmentioning
confidence: 99%
“…Today, e-shops commonly use various mechanisms for product recommendations that rely on advanced data analysis, including AI [10], but there is also considerable potential in AI-assisted user interface personalization.…”
Section: Introductionmentioning
confidence: 99%