Abstract

With the rapid development of information technology, the scale, scope and depth of database applications continue to expand, resulting in the phenomenon of "rich data and poor information." Misuse and misuse of data mining may lead to the leakage of user data, especially sensitive information. More and more people are worried about this, and even refuse to provide real data. Therefore, it is very necessary to study the application of data mining technology in personal privacy protection and material data analysis. The purpose of this article is to solve the problem of data privacy protection data mining. It mainly focuses on the research of privacy protection data mining algorithms. It uses Bayesian method analysis, theoretical analysis and logical analysis methods to carry out data mining technology in personal privacy protection and The application research in material data analysis shows that through the legal strengthening and management of data mining technology, the main reason is that data mining technology prohibits the illegal acquisition and use of other people's information on personal privacy, which can make the data mining data The security of the technology in privacy protection has been increased by 20%. In the analysis of material data, the data mining technology has greatly improved the number of processing and analysis capabilities compared to ordinary methods, which can increase the efficiency of material data analysis by 10%.

摘要

随着信息技术的飞速发展，数据库应用的规模、范围和深度不断扩大，造成了“富数据、贫信息”的现象。滥用和误用数据挖掘可能会导致用户数据，尤其是敏感信息的泄露。越来越多的人对此感到担忧，甚至拒绝提供真实数据。因此，研究数据挖掘技术在个人隐私保护和材料数据分析中的应用是非常必要的。本文的目的是解决数据隐私保护数据挖掘的问题。主要致力于隐私保护数据挖掘算法的研究。它使用贝叶斯方法分析，开展数据挖掘技术在个人隐私保护和数据分析中的应用研究表明，通过对数据挖掘技术的法律强化和管理，其主要原因是数据挖掘技术禁止非法获取和利用他人的个人隐私信息，可以使数据挖掘数据在隐私保护方面的技术安全性提高20%。在材料数据的分析中，数据挖掘技术相比普通方法大大提高了处理数量和分析能力，可以将材料数据分析的效率提高10%。