Machine Learning for Database Management Systems

N SaiTanishq
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Abstract

Machine Learning (ML) is transforming the world with research breakthroughs that are leading to the progress of every field. We are living in an era of data explosion. This further improves the output as data that can be fed to the models is more than it has ever been. Therefore, prediction algorithms are now capable of solving many of the complex problems that we face by leveraging the power of data. The models are capable of correlating a dataset and its features with an accuracy that humans fail to achieve. Bearing this in mind, this research takes an in-depth look into the of problemsolving potential of ML in the area of Database Management Systems (DBMS). Although ML hallmarks significant scientific milestones, the field is still in its infancy. The limitations of ML models are also studied in this paper.
数据库管理系统的机器学习
机器学习(ML)正在通过研究突破改变世界,这些突破正在引领各个领域的进步。我们生活在一个数据爆炸的时代。这进一步提高了输出,因为可以提供给模型的数据比以往任何时候都多。因此,预测算法现在能够通过利用数据的力量来解决我们面临的许多复杂问题。这些模型能够以人类无法达到的精度将数据集及其特征关联起来。考虑到这一点,本研究深入探讨了机器学习在数据库管理系统(DBMS)领域解决问题的潜力。尽管机器学习标志着重大的科学里程碑,但该领域仍处于起步阶段。本文还研究了机器学习模型的局限性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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