Detection method of e-commerce cluster consumption behaviour based on data feature mining

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Abstract

In order to effectively improve the accuracy and efficiency of e-commerce cluster consumption behaviour detection, an e-commerce cluster consumption behaviour detection method based on data feature mining is proposed. The concept and process of data feature mining and the e-commerce cluster consumption behaviour are analysed, and the characteristics of the e-commerce cluster consumption behaviour data with multiple characteristics are extracted. The Laplace feature mapping method is used to pre-process the extracted data features of e-commerce cluster consumption behaviour, the cyclic neural network structure is used to classify the data of e-commerce cluster consumption behaviour, and the data feature mining method is used to construct the detection model of e-commerce cluster consumption behaviour, so as to realise the detection of e-commerce cluster consumption behaviour. Experimental results show that the proposed method can effectively improve the detection accuracy and efficiency of e-commerce cluster consumption behaviour.

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APA

Yang, M. (2023). Detection method of e-commerce cluster consumption behaviour based on data feature mining. International Journal of Reasoning-Based Intelligent Systems, 15(1), 29–34. https://doi.org/10.1504/ijris.2023.128378

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