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Emerging Entity Discovery Using Web Sources

Emerging Entity Discovery Using Web Sources

Published: 2020 Januar
Herausgeber: Xiaoyan Zhu, Bing Qin, Xiaodan Zhu, Ming Liu, Longhua Qian
Buchtitel: Communications in Computer and Information Science
Ausgabe: 1134
Reihe: CCKS: China Conference on Knowledge Graph and Semantic Computing
Seiten: 175-184
Verlag: Springer
Organisation: China Conference on Knowledge Graph and Semantic Computing

Referierte Veröffentlichung


The rapidly increasing amount of entities in knowledge bases (KBs) can be beneficial for many applications, where the key issue is to link entity mentions in text with entities in the KB, also called entity linking (EL). Many methods have been proposed to tackle this problem. However, the KB can never be complete, such that emerging entity discovery (EED) is essential for detecting emerging entities (EEs) that are mentioned in text but not yet contained in the KB. In this paper, we propose a new topic-driven approach to EED by representing EEs using the context harvested from online Web sources. Experimental results show that our solution outperforms the state-of-the-art methods in terms of F1 measure for the EED task as well as Micro Accuracy and Macro Accuracy in the full EL setting.

Download: Media:CCKS_2019_paper_145.pdf
Weitere Informationen unter: Link
DOI Link: 10.1007/978-981-15-1956-7_16


Information Service Engineering