Detection method of e-commerce cluster consumption behaviour based on data feature mining Online publication date: Wed, 18-Jan-2023
by Ming Yang
International Journal of Reasoning-based Intelligent Systems (IJRIS), Vol. 15, No. 1, 2023
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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