Big Data Mining and Artificial Intelligence Based Classification Algorithm

Abstract

To solve these problems low recursive efficiency, frequent cycle and high redundancy in data classification and mining background of e-commerce under big data, this paper proposes a big data classification and Mining Grid Intelligence is based on artificial intelligence. The algorithm adopts the fast Sark architecture. On the basis of intelligent spark classification of the obtained e-commerce big data, the efficiency of data mining can be greatly improved by setting the vertical sequence controlled according to the data governance dimension. In the process of data mining, the mining patterns corresponding to all kinds of data are built, which can generate user behavior tree in the shortest time and reduce the redundancy in data mining. In data classification, the user behavior tree and its data set are mapped in turn to solve the problem of periodic convergence caused by frequent search. The results show that the algorithm consumes less time and has high accuracy in data mining.