[1] 黄昌宁, 赵海. 中文分词十年回顾[J]. 中文信息学报, 2007, 21(3): 8-19. (Huang Changning, Zhao Hai. Chinese Word Segmentation: A Decade Review [J]. Journal of Chinese Information Processing, 2007, 21(3): 8-19.)
[2] 岳金媛, 徐金安, 张玉洁. 面向专利文献的汉语分词技术研究[J]. 北京大学学报:自然科学版, 2013, 49(1): 159-164. (Yue Jinyuan, Xu Jin'an, Zhang Yujie. Chinese Word Segmentation for Patent Documents [J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 2013, 49(1): 159-164.)
[3] Ahmad K, Davies A, Fulford H, et al. What is a Term? The Semi-automatic Extraction of Terms from Text [A].//Snell-Hornby M, Pöchhacker F, Kaindl K. Translation Studies: An Interdiscipline [M]. Amsterdam: John Benjamins Publishing Company, 1994: 267-278.
[4] 翟笃风, 刘柏嵩. 政务领域本体术语的自动抽取[J]. 现代图书情报技术, 2010(4): 59-65. (Zhai Dufeng, Liu Baisong. Automatic Domain-specific Term Extraction in Administrative-domain Ontology [J]. New Technology of Library and Information Service, 2010(4): 59-65.)
[5] Pantel P, Lin D. A Statistical Corpus-based Term Extractor [C]. In: Proceedings of the 14th Biennial Conference of the Canadian Society on Computational Studies of Intelligence: Advances in Artificial Intelligence (AI'01). London: Springer-Verlag, 2001: 36-46.
[6] 刘桃, 刘秉权, 徐志明, 等. 领域术语自动抽取及其在文本分类中的应用[J]. 电子学报, 2007, 35(2): 328-332. (Liu Tao, Liu Bingquan, Xu Zhiming, et al. Automatic Domain- Specific Term Extraction and Its Application in Text Classification [J]. Acta Electronica Sinica, 2007, 35(2): 328-332.)
[7] 施水才, 王锴, 韩艳铧, 等. 基于条件随机场的领域术语识别研究[J]. 计算机工程与应用, 2013, 49(10): 147-149. (Shi Shuicai, Wang Kai, Han Yanhua, et al. Terminology Recognition Based on Conditional Random Fields [J]. Computer Engineering and Applications, 2013, 49(10): 147-149.)
[8] 岑咏华, 韩哲, 季培培. 基于隐马尔科夫模型的中文术语识别研究[J]. 现代图书情报技术, 2008(12):54-58. (Cen Yonghua, Han Zhe, Ji Peipei. Chinese Term Recognition Based on Hidden Markov Model [J]. New Technology of Library and Information Service, 2008(12): 54-58.)
[9] 荀恩东, 李晟. 采用术语定义模式和多特征的新术语及定义识别方法[J]. 计算机研究与发展, 2009, 46(1): 62-69. (Xun Endong, Li Cheng. Applying Terminology Definition Pattern and Multiple Features to Identify Technical New Term and Its Definition [J]. Journal of Computer Research and Development, 2009, 46(1): 62-69.)
[10] Berger A L, Pietray S A D, Pietray V J D. A Maximum Entropy Approach to Natural Language Processing [J]. Computational Linguistics, 1996, 22(1): 39-71.
[11] 潘正高. 基于规则和统计相结合的中文命名实体识别研究[J]. 情报科学, 2012, 30(5): 708-712, 786. (Pan Zhenggao. Research on the Recognition of Chinese Named Entity Based on Rules and Statistics [J]. Information Science, 2012, 30(5): 708-712, 786.)
[12] 孙海霞, 李军莲, 吴英杰, 等. 基于混合策略的中文生物医学领域未登录词识别研究[J]. 现代图书情报技术, 2013(1): 15-21. (Sun Haixia, Li Junlian, Wu Yingjie, et al. The Study on Out-of-vocabulary Identification of Chinese Biomedical Field Based on Hybrid Method [J]. New Technology of Library and Information Service, 2013(1): 15-21.)
[13] 黄诗琳, 郑小林, 陈德人. 针对产品命名实体识别的半监督学习方法[J]. 北京邮电大学学报, 2013, 36(2): 20-23,54. (Huang Shilin, Zheng Xiaolin, Chen Deren. A Semi- Supervised Learning Method for Product Named Entity Recognition [J]. Journal of Beijing University of Posts and Telecommunications, 2013, 36(2): 20-23, 54.)
[14] Lafferty J D, McCallum A, Pereira F C N. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data [C]. In: Proceedings of the 18th International Conference on Machine Learning (ICML'01). San Francisco: Morgan Kaufmann Publishers Inc., 2001: 282-289.
[15] Lee Y, Kim M, Lee J. Chunking Using Conditional Random Fields in Korean Texts [C]. In: Proceedings of the 2nd International Joint Conference on Natural Language Processing (IJCNLP'05). Berlin, Heidelberg: Springer- Verlag, 2005: 155-164.
[16] Ram R V S, Devi S L. Clause Boundary Identification Using Conditional Random Fields[C]. In: Proceedings of CICLing 2008, Haifa, Israel. Springer Berlin Heidelberg, 2008: 140-150.
[17] Zhou D, He Y. Learning Conditional Random Fields from Unaligned Data for Natural Language Understanding [C]. In: Proceedings of the 33rd European Conference on Advances in Information Retrieval (ECIR'11). Berlin, Heidelberg: Springer-Verlag, 2011:283-288.
[18] Zheng L, Lv X, Liu K, et al. Recognition of Chinese Personal Names Based on CRFs and Law of Names [C]. In: Proceedings of the 14th International Conference on Web Technologies and Applications (APWeb'12). Berlin, Heidelberg: Springer-Verlag, 2012:163-170.
[19] ICTCLAS汉语分词系统. ICTCLAS特色[EB/OL]. [2014-08-16]. http://www.ictclas.org/ictclas_feature.html. (ICTCLAS. Characteristic of ICTCLAS [EB/OL]. [2014-08-16]. http://www.ictclas.org/ictclas_feature.html.)
[20] 刘群, 张华平, 张浩. 计算所汉语词性标记集 Version3.0 [EB/OL]. [2014-08-16]. http://www.ictclas.org/docs/ICTPOS3.0汉语词性标记集.doc. (Liu Qun, Zhang Huaping, Zhang Hao. POS Tag Set of ICT Version3.0 [EB/OL]. [2014-08-16]. http://www.ictclas.org/docs/ICTPOS3.0汉语词性标记集. doc.)
[21] CRF++: Yet Another CRF Toolkit [EB/OL]. [2013-07-15]. http://crfpp.googlecode.com/svn/trunk/doc/index.html.
[22] 于江德, 王希杰, 樊孝忠. 基于最大熵模型的词位标注汉语分词[J]. 郑州大学学报: 理学版, 2011, 43(l): 70-74. (Yu Jiangde, Wang Xijie, Fan Xiaozhong. Chinese Word Segmentation via Word Position Tagging Based on Maximum Entropy Model [J]. Journal of Zhengzhou University: Natural Science Edition, 2011, 43(1): 70-74.)
[23] Tseng H, Chang P, Andrew G, et al. A Conditional Random Field Word Segmenter for Sighan Bakeoff 2005[C]. In: Proceedings of the 4th Sighan Workshop on Chinese Language Processing, Korea. 2005:168-171.
[24] 许晓丽, 卢志茂, 张格森. 基于条件随机场的中文命名实体识别研究[J]. 中国新技术新产品, 2009(2): 15. (Xu Xiaoli, Lu Zhimao, Zhang Gesen. Study on Conditional Random Fields Based Chinese Named Entity Recognition [J]. China New Technologies and Products, 2009(2): 15.)
[25] Zhao H, Huang C, Li M. An Improved Chinese Word Segmentation System with Conditional Random Field [C]. In: Proceedings of the 5th Sighan Workshop on Chinese Language Processing, Sydney, Australia. 2006: 108-117. |