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A Method of Biomedical Knowledge Discovery by Literature Mining Based on SPO Predications: A Case Study of Induced Pluripotent Stem Cells
Hu ZY(胡正银)1; Ceng RQ(曾荣强)1,2; Tan XC(覃筱楚)3; Wei L(隗玲)1; Zhang ZQ(张志强)1
2018-07
Conference Name14th International Conference on Machine Learning and Data Mining MLDM 2018
Source PublicationMachine Learning and Data Mining in Pattern Recognition. MLDM 2018
Conference DateJuly 15-19, 2018
Conference PlaceNew York, NY, USA
PublisherSpringer, Cham
AbstractA large amount of valuable knowledge is hidden in the vast biomedical literatures, publications, and online contents. In order to identify the previously unknown biomedical knowledge from these resources, we propose a new method of knowledge discovery based on SPO predications, which constructs a three-level SPO-semantic relation network in the considered area. We carry out the experiments in the area of induced pluripotent stem cells, and the experimental results indicate that our proposed method can significantly discover the potential biomedical knowledge in this area, and the performance analysis of this method sheds lights on the ways to further improvements.
KeywordBiomedical Knowledge Discovery Spo Induced Pluripotent Stem Cells Semantic Relation Network Community Detection
Subject Area情报技术
DOIhttps://doi.org/10.1007/978-3-319-96133-0_29
URL查看原文
Indexed ByEI
Language英语
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Document Type会议论文
Identifierhttp://ir.las.ac.cn/handle/12502/9796
Collection中国科学院成都文献情报中心_信息技术部
Affiliation1.中国科学院成都文献情报中心
2.西南交通大学
3.中国科学院广州生物医药与健康研究院
First Author Affilication中国科学院文献情报中心
Recommended Citation
GB/T 7714
Hu ZY,Ceng RQ,Tan XC,et al. A Method of Biomedical Knowledge Discovery by Literature Mining Based on SPO Predications: A Case Study of Induced Pluripotent Stem Cells[C]:Springer, Cham,2018.
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