Knowledge-oriented convolutional neural network for causal relation extraction from natural language texts

Pengfei Li, Kezhi Mao

Abstract: Highlights•Knowledge-oriented convolutional neural network (K-CNN) performs better than CNN.•Word filters capture linguistic clues of causal relation and alleviate overfitting.•Word filter selection and clustering improve the performance of K-CNN.•Semantic features improve precision and recall for complex causal relations.•Combination of knowledge and data improves the performance of deep learning model.