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題名：生物醫學語義關係抽取方法綜述
書刊名：圖書館論壇
作者：李芳／劉勝宇／劉崢
出版日期：2017
卷期：2017(6)
頁次：61-69
主題關鍵詞：語義關係抽取；生物醫學；深度學習；卷積神經網絡；自然語言處理；Semantic relation extraction；Biomedicine；Deep learning；Convolutional neural networks；Natural language processing
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深度學習在自然語言處理方面取得了顯著成效,為生物醫學領域的信息抽取帶來新的研究范式。本研究旨在系統調研生物醫學語義關系抽取方法、分析其發展歷程,為深度學習方法的進一步運用提供基礎和啟示。通過檢索Pub Med、Web of Science和IEEE數據庫,以及Bio Creative、Sem Eval等重要測評網站,遴選出具有代表性的抽取方法,并從目的、方法、數據集和效果四個維度進行分析。經過系統梳理,可將生物醫學語義關系抽取方法分為三個階段:基于知識、傳統機器學習和深度學習。將先驗知識和領域資源恰當地融入到深度學習模型中,是進一步提升語義關系抽取效果的探索方向。
Deep-learning has made remarkable achievements in natural language processing( NLP), and is bringing a new research paradigm to information extraction in biomedical field. This paper studies the extraction methods of biomedical semantic relations and analyzes its development progress and principles,which may serve as foundation for further application of deep learning. After retrieving relevant information from Pub Med,Web of Science, IEEE, and other important websites such as Bio Creative and Sem Eval, representative methods are selected and analyzed from four dimensions of purpose,approach,dataset and performance. Extraction methods of biomedical semantic relation can be divided into three stages:knowledge-based,traditional machine learningbased and deep learning-based. It is a new exploration effort to enhance the extraction effect of semantic relations by introducing prior knowledge and domain resources into deep learning model properly.
期刊論文
1.Sun, K.、Liu, H.、Yeganova, L.(2015)。Extracting Drug-Drug Interactions from Literature Using a Rich Feature-Based Linear Kernel Approach。Journal of Biomedical Informatics，55，23-30。  new window
2.BUNDSCHUS, M.、DEJORI, M.、STETTER, M.(2008)。Extraction of semantic biomedical relations from text using conditional random fields。BMC Bioinformatics，9(6)，1-14。  new window
3.ZHOU, D. Y.、ZHONG, D. Y.、HE, Y. L.(2014)。Biomedical relation extraction: from binary to complex。Computational & Mathematical Methods in Medicine，2014(3)，139-142。  new window
4.UZUNER, Ö.、SOUTH, B. R.、SHEN, S.(2011)。2010 i2b2/va challenge on concepts, assertions, and relations in clinical text。Journal of the American Medical Informatics Association，18(5)，552-556。  new window
5.COULET, A.、SHAH, N. H.、GARTEN, Y.(2010)。Using text to build semantic networks for pharmacogenomics。Journal of Biomedical Informatics，43(6)，1009-1019。  new window
6.KILICOGLU, H.、ROSEMBLAT, G.、FISZMAN, M.(2011)。Constructing a semantic predication gold standard from the biomedical literature。Bmc Bioinformatics，12(1)，1-17。  new window
7.LIU, S. Y.、TANG, B. Z.、CHEN, Q. C.(2016)。Drug-drug interaction extraction via convolutional neural networks。Computational & Mathematical Methods in Medicine，2016，1-8。  new window
8.ETZIONI, O.、BANKO, M.、SODERLAND, S.(2008)。Open information extraction from the web。Advanced Pharmaceutical Bulletin，51(12)，68-74。  new window
9.LI, G.、ROSSK, E.、ARIGHI, C. N.(2015)。Mirtex: a text mining system for miRNA-gene relation extraction。Plos Computational Biology，11(9)，1-9。  new window
10.HUANG, M.、ZHU, X.、HAO, Y.(2004)。Discovering patterns to extract protein-protein interactions from full texts。Bioinformatics，20(18)，3604-3612。  new window
11.LODHI, H.、SAUNDERS, C.、SHAWE-TAYLOR, J.(2002)。Text classification using string kernels。Journal of Machine Learning Research，2(3)，419-444。  new window
12.XU, J.、WU, Y. H.、ZHAND, Y. Y.(2016)。CD-REST: a system for extracting chemical-induced disease relation in literature。DATABASE，2016，1-9。  new window
13.LI, L.、ZHANG, P.、ZHENG, T.(2014)。Integrating semantic information into multiple kernels for protein-protein interaction extraction from biomedical literatures。Plos One，9(3)，284-287。  new window
14.BUNESCU, R. C.、MOONEY, R. J.(2005)。Subsequence kernels for relation extraction。Advances in Neural Information Processing Systems，2005，171-178。  new window
15.ZHENG, W.、LIN, H.、ZHAO, Z.(2016)。A graph kernel based on context vectors for extracting drug-drug interactions。Journal of Biomedical Informatics，61，34-43。  new window
16.QIAN, L.、ZHOU, G.(2012)。Tree kernel-based protein-protein interaction extraction from biomedical literature。Journal of Biomedical Informatics，45(3)，535-543。  new window
17.孫茂松、劉挺、姬東鴻(2014)。語言計算的重要國際前沿。中文信息學報，28(1)，1-8。  延伸查詢new window
18.RINK, B.、HARABAGIU, S.、ROBERTS, K.(2011)。Automatic extraction of relations between medical concepts in clinical texts。Journal of the American Medical Informatics Association，18(5)，594-600。  new window
19.QIN, P.、XU, W.、GUO, J.(2016)。An empirical convolutional neural network approach for semantic relation classification。Neurocomputing，190，1-9。  new window
20.陳釗、徐睿峰、桂林(2015)。結合卷積神經網絡和詞語情感序列特徵的中文情感分析。中文信息學報，29(6)，172-178。  延伸查詢new window
21.HUA, L.、QUAN, C. Q.(2016)。A Shortest Dependency Path Based Convolutional Neural Network for Protein-Protein Relation Extraction。BioMed Research International，2016，1-9。  new window
22.ZHAO, Z. H.、YANG, Z. H.、LUO, L.(2016)。Drug drug interaction extraction from biomedical literature using syntax convolutional neural network。Bioinformatics，32(22)，3444-3453。  new window
會議論文
1.FRUNZA, O.、INKPEN, D.(2010)。Extraction of disease-treatment semantic relations from biomedical sentences。The Workshop on Biomedical Natural Language Processing。Association for Computational Linguistics。  new window
2.CULOTTA, A.、MCCALLUM, A.、BETZ, J.(2006)。Integrating probabilistic extraction models and data mining to discover relations and patterns in text。Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics，296-303。  new window
3.NGUYEN, T. H.、GRISHMAN, R.(2015)。Relation Extraction: Perspective from Convolutional Neural Networks。The Workshop on Vector Space Modeling for Natural Language Processing。  new window
4.HASSAN, M.、MAKKAOUI, O.、COULET, A.(2015)。Extracting disease-symptom relationships by learning syntactic patterns from dependency graphs。The 2015 Workshop on Biomedical Natural Language Processing，71-80。  new window
5.MIWA, M.、Sætre, R.、MIYAO, Y.(2009)。A Rich Feature Vector for Protein-Protein Interaction Extraction from Multiple Corpora。Conference on Empirical Methods in Natural Language Processing。  new window
6.AIROLA, A.、PYYSALO, S.、BJÖRNE, J.(2008)。A graph kernel for protein-protein interaction extraction。The Workshop on Current Trends in Biomedical Natural Language Processing。  new window
7.KIM, Y.(2014)。Convolutional neural networks for sentence classification。The 2014 Conference on Empirical Methods in Natural Language Processing。  new window
8.ZHANG, Y.、MARSHALL, I.、WALLACE, B. C.(2016)。Rationale-Augmented Convolutional Neural Networks for Text Classification。Conf Empir Methods Nat Lang Process，795-804。  new window
9.WANG, P.、XU, J. M.、XU, B.(2015)。Semantic Clustering and Convolutional Neural Network for Short Text Categorization。The 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Short Papers)，352-357。  new window
10.ZENG, D.、LIU, K.、LAI, S.(2014)。Relation classification via convolutional deep neural network。The 25th International Conference on Computational Linguistics，2335-2344。  new window
學位論文
1.張宏濤(2012)。面向生物文本的實體關係自動抽取問題研究(-)。清華大學，北京。  延伸查詢new window
其他
1.EDEN, J.，LEVIT, L.，BERG, A.。Finding what works in health care: standards for systematic reviews，http://www.ncbi.nlm.nih.gov/pubmedhealth/PMH0079447/.。  new window
2.BACH, N.，BADASKAR, S.。A review of relation extraction，https://www.researchgate.net/publication/265006408_A_Review_of_Relation_Extraction.。  new window
3.ZHANG, Y.，WALLACE, B.。A sensitivity analysis of (and practitioners' guide to) convolutional neural networks for sentence classification，https://arxiv.org/pdf/1510.03820v2.pdf.。  new window
4.BRITZ, D.。Understanding Convolutional Neural Networks for NLP，http://www.wildml.com/2015/11/understanding-convolutionalneural-networks-for-nlp/.。  new window
 
 
 
 
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