INFER: Distilling knowledge from human-generated rules with uncertainty for STINs

Jiacheng Liu, Feilong Tang, Yanmin Zhu, Jiadi Yu, Long Chen, Ming Gao

Abstract: Highlights•We propose a new paradigm INFER that can effectively use human intelligence.•We model the uncertain rules that contain more informative knowledge.•We design a new knowledge distillation algorithm to extract knowledge from the obtained rule set.•Experimental results demonstrate INFER outperforms alternative benchmarks.