Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Moon, Taesun"'
Relation extraction (RE) is one of the most important tasks in information extraction, as it provides essential information for many NLP applications. In this paper, we propose a cross-lingual RE approach that does not require any human annotation in
Externí odkaz:
http://arxiv.org/abs/2010.08652
Named Entity Recognition (NER) is an essential precursor task for many natural language applications, such as relation extraction or event extraction. Much of the NER research has been done on datasets with few classes of entity types (e.g. PER, LOC,
Externí odkaz:
http://arxiv.org/abs/2009.07317
The task of event detection and classification is central to most information retrieval applications. We show that a Transformer based architecture can effectively model event extraction as a sequence labeling task. We propose a combination of senten
Externí odkaz:
http://arxiv.org/abs/2009.07188
Information extraction is an important task in NLP, enabling the automatic extraction of data for relational database filling. Historically, research and data was produced for English text, followed in subsequent years by datasets in Arabic, Chinese
Externí odkaz:
http://arxiv.org/abs/1912.01389
Autor:
Moon, Taesun, Ph. D.
In this dissertation, we introduce a graph-based model of instance-based, usage meaning that is cast as a problem of probabilistic inference. The main aim of this model is to provide a flexible platform that can be used to explore multiple hypotheses
Externí odkaz:
http://hdl.handle.net/2152/ETD-UT-2011-08-4143
Autor:
Moon, Taesun, Ph. D.
A knowledge of morphology can be useful for many natural language processing systems. Thus, much effort has been expended in developing accurate computational tools for morphology that lemmatize, segment and generate new forms. The most powerful and
Externí odkaz:
http://hdl.handle.net/2152/19158
Autor:
Qazvinian, Vahed, Radev, Dragomir R., Mohammad, Saif M., Dorr, Bonnie, Zajic, David, Whidby, Michael, Moon, Taesun
Publikováno v:
Journal Of Artificial Intelligence Research, Volume 46, pages 165-201, 2013
Researchers and scientists increasingly find themselves in the position of having to quickly understand large amounts of technical material. Our goal is to effectively serve this need by using bibliometric text mining and summarization techniques to
Externí odkaz:
http://arxiv.org/abs/1402.0556
This paper describes the past, present, and future of a remotely-sited, community-based language documentation project near the border between Namibia and Botswana, where the Ju|’hoan (ktz) and X’ao-’aen (aue) languages are spoken. The paper pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f92954e38da1c5ec29ff4fa554550c73
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