Search (9 results, page 1 of 1)

Leroy, G.; Chen, H.: Genescene: an ontology-enhanced integration of linguistic and co-occurrence based relations in biomedical texts (2005) 0.04

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Date: 22. 7.2006 14:26:01
Source: Journal of the American Society for Information Science and Technology. 56(2005) no.5, S.457-468
Year: 2005

Hu, P.J.-H.; Lin, C.; Chen, H.: User acceptance of intelligence and security informatics technology : a study of COPLINK (2005) 0.01

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Source: Journal of the American Society for Information Science and Technology. 56(2005) no.3, S.235-244
Year: 2005

Chen, H.: Intelligence and security informatics : Introduction to the special topic issue (2005) 0.01

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Source: Journal of the American Society for Information Science and Technology. 56(2005) no.3, S.217-220
Year: 2005

Suakkaphong, N.; Zhang, Z.; Chen, H.: Disease named entity recognition using semisupervised learning and conditional random fields (2011) 0.01
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Abstract

Information extraction is an important text-mining task that aims at extracting prespecified types of information from large text collections and making them available in structured representations such as databases. In the biomedical domain, information extraction can be applied to help biologists make the most use of their digital-literature archives. Currently, there are large amounts of biomedical literature that contain rich information about biomedical substances. Extracting such knowledge requires a good named entity recognition technique. In this article, we combine conditional random fields (CRFs), a state-of-the-art sequence-labeling algorithm, with two semisupervised learning techniques, bootstrapping and feature sampling, to recognize disease names from biomedical literature. Two data-processing strategies for each technique also were analyzed: one sequentially processing unlabeled data partitions and another one processing unlabeled data partitions in a round-robin fashion. The experimental results showed the advantage of semisupervised learning techniques given limited labeled training data. Specifically, CRFs with bootstrapping implemented in sequential fashion outperformed strictly supervised CRFs for disease name recognition. The project was supported by NIH/NLM Grant R33 LM07299-01, 2002-2005.

Chung, W.; Chen, H.: Browsing the underdeveloped Web : an experiment on the Arabic Medical Web Directory (2009) 0.01

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Date: 22. 3.2009 17:57:50

Zhu, B.; Chen, H.: Information visualization (2004) 0.01

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Source: Annual review of information science and technology. 39(2005), S.139-177

Carmel, E.; Crawford, S.; Chen, H.: Browsing in hypertext : a cognitive study (1992) 0.01

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Source: IEEE transactions on systems, man and cybernetics. 22(1992) no.5, S.865-884

Zheng, R.; Li, J.; Chen, H.; Huang, Z.: ¬A framework for authorship identification of online messages : writing-style features and classification techniques (2006) 0.01

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Date: 22. 7.2006 16:14:37

Hu, D.; Kaza, S.; Chen, H.: Identifying significant facilitators of dark network evolution (2009) 0.01

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Date: 22. 3.2009 18:50:30

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