Semi-supervised learning of causal relations in biomedical scientific discourse
نویسندگان
چکیده
منابع مشابه
Semi-supervised learning of causal relations in biomedical scientific discourse
BACKGROUND The increasing number of daily published articles in the biomedical domain has become too large for humans to handle on their own. As a result, bio-text mining technologies have been developed to improve their workload by automatically analysing the text and extracting important knowledge. Specific bio-entities, bio-events between these and facts can now be recognised with sufficient...
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Two of the main corpora available for training discourse relation classifiers are the RST Discourse Treebank (RST-DT) and the Penn Discourse Treebank (PDTB), which are both based on the Wall Street Journal corpus. Most recent work using discourse relation classifiers have employed fully-supervised methods on these corpora. However, certain discourse relations have little labeled data, causing l...
متن کاملSemi-supervised learning for biomedical information extraction
s Seen 434 76.32 95.4 84.8 Unseen 195 34.54 73.63 47.02 Overall 629 63.43 90.89 74.72 Full papers Seen 801 74.78 94.48 83.48 Unseen 1,179 53.6 86.58 66.21 Overall 1,980 62.17 90.25 73.62 Table 2.6: Evaluation of the CRF+syntax system trained on the automatically annotated abstracts and evaluated on the abstracts and the full papers dataset. found in the dictionary from FlyBase were not found in...
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Current domain-specific information extraction systems represent an important resource for biomedical researchers, who need to process vaster amounts of knowledge in short times. Automatic discourse causality recognition can further improve their workload by suggesting possible causal connections and aiding in the curation of pathway models. We here describe an approach to the automatic identif...
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The goal of this paper is twofold. First, we aim to shed light on the need to distinguish French causal connectives which convey a semantic relation from those which convey a discourse relation. Next, we aim to put forward an analysis of coordination of causal relations, in comparison with coordination of facts. While the latter is well-known, the former has nearly never been studied.
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ژورنال
عنوان ژورنال: BioMedical Engineering OnLine
سال: 2014
ISSN: 1475-925X
DOI: 10.1186/1475-925x-13-s2-s1