Strategic Transformation of E-Commerce Big Data Classification and Mining Algorithms Based on Artificial Intelligence Era

Abstract

To solve the current problem of low accuracy and time consuming data mining and classification techniques applied to e-commerce platforms, the study proposes an e-commerce data processing model based on data mining and improved KNN classification algorithm. The model first uses dimensional control mechanism and Spark mechanism together to deeply mine the massive e-commerce data, and then uses KNN algorithm based on K-value selection strategy to classify the mined data. The performance comparison experiments of the data mining algorithms show that the mining time of the proposed data mining algorithm is 4.6 min and the mining error rate is 4.2%, both of which are better than the other two data mining algorithms. Comparative experiments on the improved KNN algorithm showed that the classification recognition rate of the KNN algorithm based on the K-value selection strategy was 97.3% and the classification time was 27.3 seconds, both of which were better than the other two classification algorithms. The proposed method not only improves the accuracy of e-commerce data classification and provides data support for the accurate marketing of e-commerce platforms, but also provides new ideas for the strategic transformation of e-commerce platforms.