Cross-Scenario Inference Based Event-Event Relation Detection

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Abstract

Event-Event Relation Detection (RD 2e) aims to detect the relations between a pair of news events, such as Causal relation between Criminal and Penal events. In general, RD 2e is a challenging task due to the lack of explicit linguistic feature signaling the relations. We propose a cross-scenario inference method for RD 2e. By utilizing conceptualized scenario expression and graph-based semantic distance perception, we retrieve semantically similar historical events from Gigaword. Based on explicit relations of historical events, we infer implicit relations of target events by means of transfer learning. Experiments on 10 relation types show that our method outperforms the supervised models.

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Hong, Y., Zhang, J., Song, R., & Yao, J. (2018). Cross-Scenario Inference Based Event-Event Relation Detection. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11109 LNAI, pp. 257–267). Springer Verlag. https://doi.org/10.1007/978-3-319-99501-4_22

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