大数据视角下的因果性与相关性问题研究
A Study on Causality and Correlation from the Perspective of Big Data

大数据研究中对因果性与相关性的探讨已成为当前的焦点议题，因果性的追求曾在科学的发展过程中扮演了重要角色，但在现代科学实践中却遭遇了许多挑战。与此同时，相关性凭借其高效的数据处理优势，展现出广泛的社会应用前景。本文深入探讨了科学领域中因果性与相关性的本质，并对其理论局限性进行了深刻反思。最终，在大数据的语境中揭示了因果性与相关性之间的内在联系，并据此提出了一种整合因果性与相关性的策略。
The discussion of causality and relevance in big data research has become the current focus of issues. The pursuit of causality has played an important role in the development process of science, but it has encountered many challenges in modern science practice. At the same time, relevance, with its advantages of efficient data processing, shows a wide range of social application prospects. This paper explores the nature of causality and relevance in science and deeply reflects on its theoretical limitations. Finally, the internal link between causality and correlation is revealed in the context of big data, and a strategy to integrate causality and correlation is proposed accordingly.