| [1] 赵鹏, 蔡庆生, 王清毅, 等. 一种基于复杂网络特征的中文文档关键词抽取算法[J]. 模式识别与人工智能, 2007, 20(6): 827-831. (Zhao Peng, Cai Qingsheng, Wang Qingyi, et al. An Automatic Keyword Extraction of Chinese Document Algorithm Based on Complex Network Features [J]. Pattern Recognition and Artificial Intelligence, 2007, 20(6): 827-831.)
[2] Dumais S, Platt J, Heckerman D, et al. Inductive Learning Algorithms and Representations for Text Categorization [C]. In: Proceedings of the 7th International Conference on Information and Knowledge Management (CIKM'98). New York: ACM, 1998: 148-155.
[3] Apté C, Damerau F, Weiss S M. Automated Learning of Decision Rules for Text Categorization [J]. ACM Transactions on Information Systems, 1994, 12(3): 233-251.
[4] Joachims T. A Probabilistic Analysis of the Rocchio Algorithm with TFIDF for Text Categorization [C]. In: Proceedings of the 14th International Conference on Machine Learning (ICML'97). San Francisco: Morgan Kaufmann Publishers Inc., 1997: 143-151.
[5] Yang Y, Pedersen J O. A Comparative Study on Feature Selection in Text Categorization [C]. In: Proceedings of the 14th International Conference on Machine Learning (ICML'97). San Francisco: Morgan Kaufmann Publishers Inc., 1997: 412-420.
[6] Church K W, Hanks P. Word Association Norms, Mutual Information, and Lexicography [J]. Computational Linguistics, 1990, 16(1): 22-29.
[7] Quinlan J R. Induction of Decision Trees [J]. Machine Learning, 1986, 1(1): 81-106.
[8] Mesleh A M A. Chi Square Feature Extraction Based SVMs Arabic Language Text Categorization System [J]. Journal of Computer Science, 2007, 3(6): 430-435.
[9] 张玉芳, 万斌候, 熊忠阳. 文本分类中的特征降维方法研究[J]. 计算机应用研究, 2012, 29(7): 2541-2543. (Zhang Yufang, Wan Binhou, Xiong Zhongyang. Research on Feature Dimension Reduction in Text Classification [J]. Application Research of Computers, 2012, 29(7): 2541-2543.)
[10] 邹加棋, 陈国龙, 郭文忠. 基于图模型的中文文档分类研究[J]. 小型微型计算机系统, 2006, 27(4): 754-757. (Zou Jiaqi, Chen Guolong, Guo Wenzhong. Research on Chinese Document Classification Based on Graph Model [J]. Mini- Micro Systems, 2006, 27(4): 754-757.)
[11] 孟海东, 张炼, 吕海林. 基于图模型的文本分类方法的研究[J]. 计算机与现代化, 2010 (9): 38-40, 44. (Meng Haidong, Zhang Lian, Lv Hailin. Research on Document Classification Method Based on Graph Model [J]. Computer and Modernization, 2010(9): 38-40, 44.)
[12] 赵辉, 刘怀亮, 张倩. 一种基于复杂网络的中文文本分类算法[J]. 情报学报, 2012, 31(11): 1179-1186. (Zhao Hui, Liu Huailiang, Zhang Qian. A Chinese Text Classification Algorithm Based on Complex Network [J]. Journal of the China Society for Scientific and Technical Information, 2012, 31(11): 1179-1186.)
[13] Liu H. The Complexity of Chinese Syntactic Dependency Networks [J]. Physica A: Statistical Mechanics and Its Applications, 2008, 387(12): 3048-3058.
[14] Liu G, Zhai Z. Research on Keywords Extraction of Chinese Documents Based on TEXT-NET [C]. In: Proceedings of 2011 International Conference on Electric Information and Control Engineering (ICEICE), Wuhan, China. IEEE, 2011: 6074- 6077.
[15] Hensman S. Construction of Conceptual Graph Representation of Texts [C]. In: Proceedings of the Student Research Workshop at HLT-NAACL 2004. Stroudsburg: Association for Computational Linguistics, 2004: 49-54.
[16] 谢凤宏, 张大为, 黄丹, 等. 基于加权复杂网络的文本关键词提取[J]. 系统科学与数学, 2010, 30(11): 1592-1596. (Xie Fenghong, Zhang Dawei, Huang Dan, et al. Keywords Extraction Based on Weighted Complex Network [J]. Journal of Systems Science and Mathematical Sciences, 2010, 30(11): 1592-1596.)
[17] 吕西安·泰尼埃尔. 结构句法基础[G]. 北京: 中国人民大学语言文学系, 1987. (Tesniere L. The Basis of Structure Syntax [G]. Beijing: Language and Literature Department of Renmin University of China, 1987.)
[18] 李彬, 刘挺, 秦兵, 等. 基于语义依存的汉语句子相似度计算[J]. 计算机应用研究, 2003, 20(12): 15-17. (Li Bin, Liu Ting, Qin Bing, et al. Chinese Sentence Similarity Computing Based on Semantic Dependency Relationship Analysis [J]. Application Research of Computers, 2003, 20(12): 15-17.)
[19] 王鹏, 樊兴华. 中文文本分类中利用依存关系的实验研究[J]. 计算机工程与应用, 2010, 46(3): 131-133, 141. (Wang Peng, Fan Xinghua. Study on Chinese Text Classification Based on Dependency Relation [J]. Computer Engineering and Applications, 2010, 46(3): 131-133, 141.)
[20] Che W, Li Z, Liu T. LTP: A Chinese Language Technology Platform [C]. In: Proceedings of the 23rd International Conference on Computational Linguistics: Demonstrations, Beijing, China. Stroudsburg: Association for Computational Linguistics, 2010: 13-16.
[21] Matsuo Y, Ohsawa Y, Ishizuka M. A Document as a Small World[A]//New Frontiers in Artificial Intelligence [M]. Springer Berlin Heidelberg, 2001: 444-448.
[22] 刘知远, 郑亚斌, 孙茂松. 汉语依存句法网络的复杂网络性质[J]. 复杂系统与复杂性科学, 2008, 5(2): 37-45. (Liu Zhiyuan, Zheng Yabin, Sun Maosong. Complex Network Properties of Chinese Syntactic Dependency Network [J]. Complex Systems and Complexity Science, 2008, 5(2): 37-45.)
[23] 刘海涛. 汉语句法网络的复杂性研究[J]. 复杂系统与复杂性科学, 2007, 4(4): 38-44. (Liu Haitao. The Complexity of Chinese Syntactic Network[J]. Complex Systems and Complexity Science, 2007, 4(4): 38-44.)
[24] 刘旭. 克里米亚公投结束 民调显示93%选民赞成入俄[EB/OL]. (2014-03-17). http://news.sohu.com/20140317/ n396701134.shtml. (Liu Xu. The End of the Crimean Referendum Poll Shows 93% of Voters is in Favor of the Entry of Russia [EB/OL]. (2014-03-17). http://news.sohu. com/20140317/n396701134.shtml.)
[25] The Open Graph Viz Platform [EB/OL]. [2014-03-05]. http:// www.gephi.org.
[26] 张巍. 基于PageRank算法的搜索引擎优化策略研究[D]. 成都: 四川大学, 2005. (Zhang Wei. Research on Optimizing Strategies of Search Engine Based on PageRank Algorithm [D]. Chengdu: Sichuan University, 2005.)
[27] 陈小飞, 王轶彤, 冯小军. 一种基于网页质量的PageRank算法改进[J]. 计算机研究与发展, 2009, 46(S): 381-387. (Chen Xiaofei, Wang Yitong, Feng Xiaojun. An Improvement of PageRank Algorithm Based on Page Quality [J]. Journal of Computer Research and Development, 2009, 46(S): 381-387.)
[28] 夏天. 词语位置加权TextRank的关键词抽取研究[J]. 现代图书情报技术, 2013(9): 30-34. (Xia Tian. Study on Keyword Extraction Using Word Position Weighted TextRank[J].New Technology of Library and Information Service, 2013(9): 30-34.)
[29] Zhang H, Yu H, Xiong D, et al. HHMM-based Chinese Lexical Analyzer ICTCLAS[C]. In: Proceedings of the 2nd SIGHAN Workshop on Chinese Language Processing (SIGHAN'03), Sapporo, Japan. Stroudsburg: Association for Computational Linguistics, 2003: 184-187.
[30] The Stanford Parser: A Statistical Parser [EB/OL]. [2014-05- 29]. http://nlp.stanford.edu/software/lex-parser.shtml#Download.
[31] 陈果, 胡昌平. 科研领域关键词网络的结构特征与启示——基于图情学科的实证研究[J]. 现代图书情报技术, 2014(7-8): 84-91. (Chen Guo, Hu Changping. Research on the Structural Features of Keyword Network of Scientific Research Areas: An Empirical Study of LIS [J]. New Technology of Library and Information Service, 2014(7-8): 84-91.) |
