Research on Big Data Mining and Application Based on Roll Up and Drill Down Techniques

Research on Big Data Mining and Application Based on Roll Up and Drill Down Techniques

연구 분야: Databases

학회: 2023 International Conference on New Trends in Computational Intelligence (NTCI)

To improve the efficiency of big data mining while ensuring the accuracy of mining results. Propose a big data mining method based on roll up and drill down techniques. By using roll up techniques to achieve feature aggregation, reduce the number of features, improve time efficiency, and analyze the mining results to determine the target clustering features. Drill down on the target clustering features to ensure the accuracy of the mining results. The experiment uses the independently created Mongolian medicine formula datasets as a case study to provide specific applications. The experimental results show that the time efficiency and efficiency improvement rate of mining result generation have been improved to a certain extent under various expansion data multiples, and the three error rate indicators of mining results have also been improved. Therefore, this method can not only improve the efficiency of big data mining, but also ensure the accuracy of mining results.