| Journal: | Computación y Sistemas |
| Database: | PERIÓDICA |
| System number: | 000457496 |
| ISSN: | 1405-5546 |
| Authors: | Pandian, Arun1 Mulaffer, Lamana1 Oflazer, Kemal1 AlZeyara, Amna1 |
| Institutions: | 1Carnegie Mellon University in Qatar, Doha City. Qatar |
| Year: | 2020 |
| Season: | Ene-Mar |
| Volumen: | 24 |
| Number: | 1 |
| Pages: | 5-16 |
| Country: | México |
| Language: | Inglés |
| Document type: | Artículo |
| Approach: | Aplicado, descriptivo |
| English abstract | This paper presents a neural network classifier approach to detecting precise within-document(WD) and cross-document(CD) event coreference clusters effectively using only event mention based features. Our approach does not rely on any event argument features such as semantic roles or spatio-temporal arguments and uses no sophisticated clustering approach. Experimental results on the ECB+ dataset show that our simple approach outperforms state-of-the-art methods for both within-document and cross-document event coreference resolution while producing clusters of high precision, which is useful for several downstream tasks |
| Disciplines: | Ciencias de la computación |
| Keyword: | Inteligencia artificial, Procesamiento de datos, Programación, Aprendizaje profundo, Clasificación de documentos, Eventos, Semántica, Redes neuronales |
| Keyword: | Artificial intelligence, Data processing, Programming, Deep learning, Document classification, Events, Semantics, Neural networks |
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