基于数据挖掘技术的区块链数据推荐算法

Blockchain data recommendation algorithm based on data mining technology

随着区块链技术在金融领域的应用越来越广泛,产生的交易数据和区块信息也越来越多,如何有效地管理和利用这些数据成为一个重要的问题。此次研究提出了一种基于数据挖掘技术的区块链数据推荐算法,旨在提高区块链数据推荐的精准度和效率,帮助金融监管机构更好地实现监管目标。研究将基于LightGBM算法的区块链数据推荐算法与其类似算法进行性能测试,实验结果表明,LightGBM算法的PR曲线值最大,为0.956;LightGBM算法的AUC值最高,为0.958;LightGBM算法的KS值曲线值最大,为0.7185;LightGBM算法的准确率值最高,为0.925。由此表明,此次研究算法可以提高区块链数据推荐的精准度和效率,为金融监管机构实现监管目标提供强有力的支持.

With the application of blockchain technology in the financial field,more and more transaction data and block information are generated.How to manage and utilize these data effectively has become an important issue.This study proposes a blockchain data recommendation algorithm based on data mining technology,which aims to improve the accuracy and efficiency of blockchain data recommendation and help financial regulators better achieve regulatory goals.The performance of the blockchain data recommendation algorithm based on LightGBM algorithm is tested with its similar algorithms.The experimental results show that the PR curve value of LightGBM algorithm is the largest,which is 0.956;The AUC value of LightGBM algorithm is the highest(0.958).The maximum KS value curve of LightGBM algorithm is 0.7185.The accuracy of LightGBM algorithm is the highest,which is 0.925.This shows that the research algorithm can improve the accuracy and efficiency of blockchain data recommendation,and provide strong support for financial regulators to achieve regulatory goals.