大数据相关关系及其深层因果关系意蕴

Correlation in Big Data and Its Deep Causal Meaning

大数据的信息性质及其对相关关系的凸显,促使人们对相关关系及其与因果关系的关联进行深入反思。因果概念的重新刻画及其量化展开,展示了物数据化中的因果关系际遇:在获得量的关系强度和正负性质的同时,丧失了原有的必然性和方向性。相关关系是因果派生关系。相关关系的因果派生机制决定了相关关系的或然性质,说明了相关关系的因果派生强度和因果派生层次。大数据相关关系具有深层因果关系意蕴,它意味着因果时态的展示,追溯既往的因果关系量化把握和探向未来的新因果关系创构。

The informational nature of and the highlights of correlations by big data urge people to reflect deeply on correlations and its connection with causality. The redefinition of the concept of causality and its quantificationally spreading shows the fortune of causality in the process of matter data- mation： a loss in terms of in evitability and direction as well as a gain in relationship strength and posi- tive and negative properties. Correlations are causal derivative relationships.The mechanism of causal derivative relationship determines the probabilistic nature of correlation,illustrates the strength and lev- elof causal derivation of correlation. Correlations in big data has deep causal connotations, it means the reveal of causal tense, the quantifying grasp of the causality back over the past and the creation of new causality towards future.