Recognizing Identical Events with Graph Kernels (CROSBI ID 597893)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Glavaš, Goran ; Šnajder, Jan
engleski
Recognizing Identical Events with Graph Kernels
Identifying news stories that discuss the same real-world events is important for news tracking and retrieval. Most existing approaches rely on the traditional vector space model. We propose an approach for recognizing identical real-world events based on a structured, event-oriented document representation. We structure documents as graphs of event mentions and use graph kernels to measure the similarity between document pairs. Our experiments indicate that the proposed graph-based approach can outperform the traditional vector space model, and is especially suitable for distinguishing between topically similar, yet non- identical events.
Event extraction; event graphs; graph kernels; topic detection and tracking; information extraction
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Podaci o prilogu
797-803.
2013.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
Sofija: Association for Computational Linguistics (ACL)
Podaci o skupu
51st Annual Meeting of the Association for Computational Linguistics
predavanje
04.08.2013-09.08.2013
Sofija, Bugarska