Semi-supervised Pattern Learning for Extracting Relations from Bioscience Texts

资源类型: 资源大小: 文档分类: 上传者:李德翠

文档信息

【标题】Semi-supervised Pattern Learning for Extracting Relations from Bioscience Texts

【作者】 Shilin Ding  Minlie Huang  Xiaoyan Zhu 

【关键词】Ranking Function Semi-supervised Relation Extraction Pattern Set UNlabeled Data 

【摘要】A variety of pattern-based methods have been exploited to extract biological relations from literatures. Many of them require significant domain-specific knowledge to build the patterns by hand; or a large amount of labeled data to learn the patterns automatically. In this paper; a semisupervised model is presented to combine both unlabeled and labeled data for the pattern learning procedure. First; a large amount of unlabeled data is used to generate a raw pattern set. Then it is refined in the evaluating phase by incorporating the domain knowledge provided by a relatively small labeled data. Comparative results show that labeled data; when used in conjunction with the inexpensive unlabeled data; can considerably improve the learning accuracy.

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