[1]王艳华,杨志豪,李彦鹏,等.基于监督学习和半监督学习的蛋白质关系抽取[J].江西师范大学学报(自然科学版),2013,(04):392-396.
 WANG Yan-hua,YANG Zhi-hao,LI Yan-peng,et al.Protein-Protein Interaction Extraction Based on the Combination of Supervised and Semi-Supervised Learning Method[J].Journal of Jiangxi Normal University:Natural Science Edition,2013,(04):392-396.
点击复制

基于监督学习和半监督学习的蛋白质关系抽取()
分享到:

《江西师范大学学报》(自然科学版)[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2013年04期
页码:
392-396
栏目:
出版日期:
2013-09-01

文章信息/Info

Title:
Protein-Protein Interaction Extraction Based on the Combination of Supervised and Semi-Supervised Learning Method
作者:
王艳华;杨志豪;李彦鹏;唐利娟;林鸿飞
大连理工大学计算机科学与技术学院,辽宁大连,116024;山东省农业管理干部学院机械电子工程系,山东济南,250100
Author(s):
WANG Yan-hua;YANG Zhi-hao;LI Yan-peng;TANG Li-juan;LIN Hong-fei
关键词:
文本挖掘信息抽取蛋白质关系抽取监督学习半监督学习
Keywords:
text mininginformation extractionprotein-protein interactionsupervised learningsemi-supervised learning
分类号:
TP391
文献标志码:
A
摘要:
提出了一种将监督学习和半监督学习融合的方法,并用于从文献中自动抽取蛋白质关系.在Aimed语料上的实验得到63.2;的F值,这表明该方法达到目前较好的性能.
Abstract:
An approach based on supervised learning and semi-supervised learning to automatically extract protein-protein interactions from biomedical literature has been presented.Experimental evaluations show that the method can achieve the state of art performance with 63.2% ore on the AImed corpus.

参考文献/References:

[1] Bunescu R C,Mooney R J.Subsequence kernels for relation extraction [C].MA:MIT Press,2006:171-178.
[2] Moschitti A.Making tree kernels practical for natural language processing [C].NJ:Association for Computational Linguistics,2006:113-120.
[3] Sætre R,Sagae K,Tsujii J.Syntactic features for protein-protein interaction extraction [C].Germany:CEUR,2007.
[4] Bunescu R C,Mooney R J.A shortest path dependency kernel for relation extraction [C].NJ:Association for Computational Linguistics,2005:724-731.
[5] Airola A,Pyysalo S,Bj?rne J,et al.All-paths graph kernel for proteinrotein interaction extraction with evaluation of cross corpus learning [EB/OL].
[2012-10-13].http:∥www.biomedcentral.com/1471-2105/9/S11/S2.
[6] Miwa M,Sætre R,Miyao Y,et al.A rich feature vector for protein-protein interaction extraction from multiple corpora [EB/OL]
[2012-10-15].http:∥www.aclweb.org/anthology-new/D/D09/D09-1013.pdf.
[7] Li Yanpeng,Hu Xiaohua,Lin Hongfei,et al.Learning an enriched representation from unlabeled data for protein-protein interaction extraction [EB/OL].
[2012-10-17].http:∥www.biomedcentral.com/1471-2105/11/S2/S7.
[8] Duda RO,Hart PE.Pattern classification and scene analysis [M].New York:John Wiley,1973.
[9] 刘立月,黄兆华,刘遵雄.高维数据分类中的特征降维研究 [J].江西师范大学学报:自然科学版,2012,36(2):131-134.
[10] 唐楠,杨志豪,林鸿飞,等.基于多核学习的医学文献蛋白质关系抽取 [J].计算机工程,2011,37(10):184-186.

相似文献/References:

[1]耿耘,蒋严冰,郭岩,等.基于组合验证的Web页面抽取算法研究[J].江西师范大学学报(自然科学版),2013,(02):142.
 GENG Yun,JIANG Yan-bing,GUO Yan,et al.Research of Information Extraction Algorithm Based on Compositional Verification[J].Journal of Jiangxi Normal University:Natural Science Edition,2013,(04):142.

备注/Memo

备注/Memo:
国家自然科学基金(61070098,61272373);中央高校基本科研业务费专项资金(DUT13JB09)
更新日期/Last Update: 1900-01-01