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个人信息Personal Information
教授
博士生导师
硕士生导师
性别:女
毕业院校:大连理工大学
学位:博士
所在单位:计算机科学与技术学院
学科:计算机应用技术. 计算机软件与理论
办公地点:创新大厦A930
电子邮箱:lils@dlut.edu.cn
An Unsupervised Graph Based Continuous Word Representation Method for Biomedical Text Mining
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论文类型:期刊论文
发表时间:2016-07-01
发表刊物:IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
收录刊物:SCIE、EI、Scopus
卷号:13
期号:4
页面范围:634-642
ISSN号:1545-5963
关键字:Natural language processing; machine learning; connectionism and neural nets; object representation
摘要:In biomedical text mining tasks, distributed word representation has succeeded in capturing semantic regularities, but most of them are shallow-window based models, which are not sufficient for expressing the meaning of words. To represent words using deeper information, we make explicit the semantic regularity to emerge in word relations, including dependency relations and context relations, and propose a novel architecture for computing continuous vector representation by leveraging those relations. The performance of our model is measured on word analogy task and Protein-Protein Interaction Extraction (PPIE) task. Experimental results show that our method performs overall better than other word representation models on word analogy task and have many advantages on biomedical text mining.