{"type":"ScholarlyArticle","title":"Boosting Causal Embeddings via Potential Verb-Mediated Causal Patterns","authors":[{"name":"Zhipeng Xie","slug":"zhipeng-xie","given":"Zhipeng","family":"Xie","affiliation":"Shanghai Key Laboratory of Data Science , Fudan University School of Computer Science , Fudan University"},{"name":"Feiteng Mu","slug":"feiteng-mu","given":"Feiteng","family":"Mu","affiliation":"Shanghai Key Laboratory of Data Science , Fudan University School of Computer Science , Fudan University"}],"abstract":"Existing approaches to causal embeddings rely heavily on hand-crafted high-precision causal patterns, leading to limited coverage. To solve this problem, this paper proposes a method to boost causal embeddings by exploring potential verb-mediated causal patterns. It first constructs a seed set of causal word pairs, then uses them as supervision to characterize the causal strengths of extracted verb-mediated patterns, and finally exploits the weighted extractions by those verb-mediated patterns in the construction of boosted causal embeddings. Experimental results have shown that the boosted causal embeddings outperform several state-of-the-arts significantly on both English and Chinese. As by-products, the top-ranked patterns coincide with human intuition about causality.","doi":"10.24963/ijcai.2019/266","url":"https://ijcai.org/proceedings/2019/266","pdf":"https://ijcai.org/proceedings/2019/0266.pdf","markdown":"https://ijcai.org/proceedings/2019/266.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/266","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"Knowledge Representation and Reasoning","track":"Main track","number":266,"pages":{"first":1921,"last":1927},"keywords":["Knowledge Representation and Reasoning: Action, Change and Causality"],"videos":[],"references":[{"position":1,"raw":"[Boros et al., 2014] Emanuela Boros, Romaric Besanc ¸on, Olivier Ferret, and Brigitte Grau. 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