Naslov
Recognizing Identical Events with Graph Kernels

Autori
Glavaš, Goran ; Šnajder, Jan

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) / - Sofija : Association for Computational Linguistics (ACL), 2013, 797-803

Skup
51st Annual Meeting of the Association for Computational Linguistics

Mjesto i datum
Sofija, Bugarska, 04.08.2013. - 09.08.2013

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Event extraction; event graphs; graph kernels; topic detection and tracking; information extraction

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

POVEZANOST RADA