Oct 13, 2020 · Joint-event-extraction, which extracts structural information (i.e., entities or triggers of events) from unstructured real-world corpora, has ...

Moreover, since the connected entities and triggers naturally form a heterogeneous information network (HIN), we leverage the latent pattern along meta-paths ...

Recently, co-clustering algorithms are widely used in heterogeneous information networks mining, and the distance metric is still a challenging problem. Bregman ...

Cross-Supervised Joint-Event-Extraction with. Heterogeneous Information Networks. Yue Wang1,5, Zhuo Xu1, Lu Bai1, Yao Wan2, Lixin Cui1, Qian Zhao5, Edwin R ...

Cross-Supervised Joint-Event-Extraction with Heterogeneous Information Networks · no code implementations • 13 Oct 2020 • Yue Wang, Zhuo Xu, Lu Bai, Yao Wan ...

Cross-Supervised Joint-Event-Extraction with Heterogeneous Information Networks ... extraction from Unstructured corpora using Structural Information Network.

This work proposes to do event extraction in a joint framework with bidirectional recurrent neural networks, thereby benefiting from the advantages of the ...

Cross-Supervised Joint-Event-Extraction with Heterogeneous Information Networks · no code implementations • 13 Oct 2020 • Yue Wang, Zhuo Xu, Lu Bai, Yao Wan ...

This paper proposes a novel approach that models the dependencies among variables of events, entities, and their relations, and performs joint inference of ...

Joint-event-extraction, which extracts structural information (i.e., entities or triggers of events) from unstructured real-world corpora, has attracted ...