CausalLP: Learning causal relations with weighted knowledge graph link prediction

Understand

Causal networks are useful in a wide variety of applications, from medical diagnosis to root-cause analysis in manufacturing.

• In practice, however, causal networks are often incomplete with missing causal relations.
• This paper presents a novel approach, called CausalLP, that formulates the issue of incomplete causal networks as a knowledge graph completion problem.
• More specifically, the task of finding new causal relations in an incomplete causal network is mapped to the task of knowledge graph link prediction.