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优先出版 袁凯琦,等:医学知识图谱构建技术与研究进展 第35卷第7期 Informatics, 2014, 47(2): 1-10 Pac Symp Biocomput. 2000, 5: 529-540 [26] Kazama J, Makino T, Ohta Y, et al. Tuning support vector machines for [40] Khoo C SG Chan S, Niu Y Extracting causal knowledge from a medical biomedical named entity recognition [CM Proc of Workshop on Natural language Processing in the Biomedical Domain-Volume 3. Association for Association for Computational Linguistics. Association for Computational Computational Linguistics, 2002: 1-8 Linguistics, 2000: 336-343 门 Zhou, G, Zhang. J., Su. J. et al. Recognizing names in biomedical texts:A41]王昊奋,张金康,程小军.中文开放链接医疗数据的构建卩中国数 machine learning approach [J]. Bioinformatics, 2004, 20(7), pp. 1178 字医学,2013,8(4)5-8 42]徐绪堪,房道伟,蒋勳,等。知识组织中知识粒度化表示和規范化研究 8]Chen L, Friedman C. C: Extracting phenotypic information from the 图书情报知识,2014,2014(6101-106 literature via natural language processing I. Studies in Health Technology43]庄严,李国良,冯建华,知识库实体对齐技术综述囚计算机研究与 & Informatics,2004,107(2:758-62. 发展,2016,53(1):165-192 129] Liang L, Wang K, Meng D, et al. Active self-paced learning for [44 Fellegi I P, Sunter A B A Theory for Record Linkage [J]. Journal of the ost-effective and progressive face identification J]. IEEE Trans American Statistical Association, 1969, 64(328): 1183-1210 Pattern Analysis Machine Intelligence, 2017, PP(99): 1-1 [45] Cochinwala M, Kurien V, Lalk Gi et al. Efficient data reconciliation UJI [30] Collobert R, Weston J, Bottou L, et al. Natural Language Processing Information Sciences An International Journal, 2001, 137(1-4): 1-15 (Almost) from Scratch [ J] Journal of Machine Learning Research, 2011, [46] Elfeky M G, verykios V S, Elmagarmid A K. TAILOR: A Record Linkage Tool Box [Cy/ Proc of International Conference on Data Engineering. [31] Sahu S K, Anand A Recurrent neural network for disease name 2002:17-28 recognition using domain invariant features ICy/ Proc of Meeting of the [47] Christen P. Automatic Training Example Selection for Scalable Association for Computationa Linguistics. 2016 Unsupervised Record Linkage [M]/ Advances in Knowledge Discovery [32] Wei Q, Chen T, Xu R, et al. Disease named entity recognition by and Data Mining. 148 Chen Z, Kalashnikov D V, Mehrotra S. Exploiting context analysis for networks [ J). Database the Journal of Biological Databases Curation, combining multiple entity resolution systems [Cy Proc of ACM SIGMOD 2016,2016 Intemational Conference on Management of Data. 2009: 207-218 3] Jagannatha A, Yu H Structured prediction models for RNN based sequence [ 49] Ravikumar P, Cohen ww. A Hierarchical Graphical Model for Record labeling in clinical text [Cy/ Proc of Conference on Empirical Methods in Linkage [ J]. 2012, 24(2) Natural Language Processing. 2016: 856-86 50J Li J, Wang Z, Zhang X, et al. Large scale instance matching via multiple [34] Organization W H. The ICD-10 classification of mental and behavioural indexes and candidate selection [J]. Knowledge-Based Systems, 2013, 50 disorders: clinical descriptions and diagnostic guidelines J). Geneva World (30:112-120. 51] Bhattacharya L, Getoor L. Collective entity resolution in relational data JJ [35] Uzuner O, Mailoa J, Ryan R, et al. Semantic relations for problem-oriented CM Transactions on Knowledge Discovery from Data(TKDD) medical records J]. Artificial intelligence in medicine, 2010, 50(2): 63-73 [36] Frunza O, Inkpen D. Extraction of disease-treatment semantic relations [52 Lacoste-Julien S, Palla K, Davies A, et al. Sigma: Simple greedy matching from biomedical sentences [C]/ Proc of Workshop on Biomedical Natural for aligning large knowledge bases [C Proc of the 19th ACM SIGKDD Language Processing. Association for Computational Linguistics, 2010 International Conference on Knowledge Discovery And Data Mining ACM,2013:572-580 137) Abacha A B, Zweigenbaum P. A hybrid approach for the extraction of [53] Tang J, Li J, Liang B, et al. Using Bayesian decision for ontology mapping semantic relations from MEDLINE abstracts (CHi Proc of Intemational UJI. Web Semantics: Science, Services and Agents on the World Wide Web Conference on Intelligent Text Processing and Computational Linguistics 106,4(4)243-262. [38] Bruijn B D, Cherry C, Kiritchenko S, et al. Machine-learned solutions for resolution [Cy/ Proc of SIAM International Conference on Data Mining. three stages of clinical information extraction: the state of the art at 12b2 Society for Industrial and Applied Mathematics. 2006: 47-58. 2010 []. Journal of the American Medical Informatics Association, 2011, [55] Mccallum A, Wellner B Conditional Models of ldentity Uncertainty with 18(5):557-62 [39]Stapley B J, Benoit G Biobibliometrics: information retrieval and [ 56] Domingos P. Multi-Relational Record Linkage [). Journal of Neuroscience, visualization from co-occurrences of gene names in Medline abstracts ICy 004,25(25):1113-21优先出版 袁凯琦,等:医学知识图谱构建技术与研究进展 第 35 卷第 7 期 Informatics, 2014, 47 (2): 1-10. [26] Kazama J, Makino T, Ohta Y, et al. Tuning support vector machines for biomedical named entity recognition [C]// Proc of Workshop on Natural language Processing in the Biomedical Domain-Volume 3. Association for Computational Linguistics, 2002: 1-8. [27] Zhou, G. , Zhang, J. , Su, J. et al. Recognizing names in biomedical texts: A machine learning approach [J]. Bioinformatics, 2004, 20 (7) , pp. 1178 – 1190. [28] Chen L, Friedman C. C: Extracting phenotypic information from the literature via natural language processing [J]. Studies in Health Technology & Informatics, 2004, 107 (2): 758-62. [29] Liang L, Wang K, Meng D, et al. Active self-paced learning for cost-effective and progressive face identification [J]. IEEE Trans on Pattern Analysis & Machine Intelligence, 2017, PP (99): 1-1. [30] Collobert R, Weston J, Bottou L, et al. Natural Language Processing (Almost) from Scratch [J]. Journal of Machine Learning Research, 2011, 12 (1): 2493-2537. [31] Sahu S K, Anand A. Recurrent neural network models for disease name recognition using domain invariant features [C]// Proc of Meeting of the Association for Computationa Linguistics. 2016. [32] Wei Q, Chen T, Xu R, et al. Disease named entity recognition by combining conditional random fields and bidirectional recurrent neural networks [J]. Database the Journal of Biological Databases & Curation, 2016, 2016. [33] Jagannatha A, Yu H. Structured prediction models for RNN based sequence labeling in clinical text [C]// Proc of Conference on Empirical Methods in Natural Language Processing. 2016: 856-865. [34] Organization W H. The ICD-10 classification of mental and behavioural disorders: clinical descriptions and diagnostic guidelines [J]. Geneva World Health Organization, 1992, 10 (2): 86–92. [35] Uzuner O, Mailoa J, Ryan R, et al. Semantic relations for problem-oriented medical records [J]. Artificial intelligence in medicine, 2010, 50 (2): 63-73. [36] Frunza O, Inkpen D. Extraction of disease-treatment semantic relations from biomedical sentences [C]// Proc of Workshop on Biomedical Natural Language Processing. Association for Computational Linguistics, 2010: 91-98. [37] Abacha A B, Zweigenbaum P. A hybrid approach for the extraction of semantic relations from MEDLINE abstracts [C]// Proc of International Conference on Intelligent Text Processing and Computational Linguistics. Springer Berlin Heidelberg, 2011: 139-150. [38] Bruijn B D, Cherry C, Kiritchenko S, et al. Machine-learned solutions for three stages of clinical information extraction: the state of the art at i2b2 2010 [J]. Journal of the American Medical Informatics Association, 2011, 18 (5): 557-62. [39] Stapley B J, Benoit G. Biobibliometrics: information retrieval and visualization from co-occurrences of gene names in Medline abstracts [C]// Pac Symp Biocomput. 2000, 5: 529-540. [40] Khoo C S G, Chan S, Niu Y. Extracting causal knowledge from a medical database using graphical patterns [C]// Proc of the 38th Annual Meeting on Association for Computational Linguistics. Association for Computational Linguistics, 2000: 336-343. [41] 王昊奋, 张金康, 程小军. 中文开放链接医疗数据的构建 [J]. 中国数 字医学, 2013, 8 (4): 5-8. [42] 徐绪堪, 房道伟, 蒋勋, 等. 知识组织中知识粒度化表示和规范化研究 [J]. 图书情报知识, 2014, 2014 (6): 101-106, 90. [43] 庄严, 李国良, 冯建华. 知识库实体对齐技术综述 [J]. 计算机研究与 发展, 2016, 53 (1): 165-192. [44] Fellegi I P, Sunter A B. A Theory for Record Linkage [J]. Journal of the American Statistical Association, 1969, 64 (328): 1183-1210. [45] Cochinwala M, Kurien V, Lalk G, et al. Efficient data reconciliation [J]. Information Sciences An International Journal, 2001, 137 (1–4): 1-15. [46] Elfeky M G, Verykios V S, Elmagarmid A K. TAILOR: A Record Linkage Tool Box [C]// Proc of International Conference on Data Engineering. 2002: 17-28. [47] Christen P. Automatic Training Example Selection for Scalable Unsupervised Record Linkage [M]// Advances in Knowledge Discovery and Data Mining. Berlin: Springer, 2008: 511-518. [48] Chen Z, Kalashnikov D V, Mehrotra S. Exploiting context analysis for combining multiple entity resolution systems [C]// Proc of ACM SIGMOD International Conference on Management of Data. 2009: 207-218. [49] Ravikumar P, Cohen W W. A Hierarchical Graphical Model for Record Linkage [J]. 2012, 24 (2) . [50] Li J, Wang Z, Zhang X, et al. Large scale instance matching via multiple indexes and candidate selection [J]. Knowledge-Based Systems, 2013, 50 (30): 112-120. [51] Bhattacharya I, Getoor L. Collective entity resolution in relational data [J]. ACM Transactions on Knowledge Discovery from Data (TKDD) , 2007, 1 (1): 5. [52] Lacoste-Julien S, Palla K, Davies A, et al. Sigma: Simple greedy matching for aligning large knowledge bases [C]// Proc of the 19th ACM SIGKDD International Conference on Knowledge Discovery And Data Mining. ACM, 2013: 572-580. [53] Tang J, Li J, Liang B, et al. Using Bayesian decision for ontology mapping [J]. Web Semantics: Science, Services and Agents on the World Wide Web, 2006, 4 (4): 243-262. [54] Bhattacharya I, Getoor L. A latent dirichlet model for unsupervised entity resolution [C]// Proc of SIAM International Conference on Data Mining. Society for Industrial and Applied Mathematics. 2006: 47-58. [55] Mccallum A, Wellner B. 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