[1] 张鸣. 知识服务方式之一——构建学科专题知识库[J]. 图书馆学刊, 2006, 28(3): 108-110. (Zhang Ming. One Model of Knowledge Service in Network Era——Constructing Knowledge Storehouse of Specialized Subject [J]. Journal of Library Science, 2006, 28(3): 108-110.)
[2] 钱智勇. 基于本体的专题域知识库系统设计与实现——以张謇研究专题知识库系统实现为例[J]. 情报理论与实践, 2006, 29(4): 476-479. (Qian Zhiyong. Design & Realization of the Ontology-based Subject Domain Knowledge Base System [J]. Information Studies: Theory & Application, 2006, 29(4): 476-479.)
[3] 闫洪森, 张野, 孙娜, 等. 基于本体的知识库构建方法[J]. 情报科学, 2007, 25(9): 1398-1400, 1408. (Yan Hongsen, Zhang Ye, Sun Na, et al. Construction Method of Knowledge Database Based on Ontology[J]. Information Science, 2007, 25(9): 1398-1400, 1408.)
[4] 许鑫, 郭金龙. 基于领域本体的专题库构建——以中华烹饪文化知识库为例[J]. 现代图书情报技术, 2013(12): 2-9. (Xu Xin, Guo Jinlong. Construction of Subject Knowledge Base ——Taking the Domain of Chinese Cuisine Culture as an Example [J]. New Technology of Library and Information Service, 2013(12): 2-9.)
[5] 洪韵佳, 许鑫. 基于领域本体的知识库多层次文本聚类研究——以中华烹饪文化知识库为例[J]. 现代图书情报技术, 2013(12): 19-26. (Hong Yunjia, Xu Xin. Study on Multi-level Text Clustering for Knowledge Base Based on Domain Ontology——Taking Knowledge Base of Chinese Cuisine Culture as an Example [J]. New Technology of Library and Information Service, 2013(12): 19-26.)
[6] Don A, Zheleva E, Gregory M, et al. Discovering Interesting Usage Patterns in Text Collections: Integrating Text Mining with Visualization[C]. In: Proceedings of the 16th ACM Conference on Information and Knowledge Management (CIKM'07). New York: ACM, 2007: 213-222.
[7] Luo D, Yang J, Krstajic M, et al. EventRiver: Visually Exploring Text Collections with Temporal References [J]. IEEE Transactions on Visualization and Computer Graphics, 2012, 18(1): 93-105.
[8] Pearson K. Onlines and Planes of Closest Fit to Systems of Points in Space [J]. Philosophical Magazine, 1901, 2(6): 559-572.
[9] Scholkopf B, Smola A, Muller K. Nonlinear Component Analysis as a Kernel Eigenvalue Problem[J]. Neural Computation, 1998, 10(5): 1299-1319.
[10] 冯燕, 何明一, 宋江红, 等. 基于独立成分分析的高光谱图像数据降维及压缩[J]. 电子与信息学报, 2007, 29(12): 2871-2875. (Feng Yan, He Mingyi, Song Jianghong, et al. ICA-Based Dimensionality Reduction and Compression of Hyperspectral Images [J]. Journal of Electronics & Information Technology, 2007, 29(12): 2871-2875.)
[11] Pu J, Kalyanaraman Y, Jayanti S, et a1. Navigation and Discovery in 3D CAD Repositories [J]. IEEE Computer Graphics and Applications, 2007, 27(4): 38-47.
[12] Jee T, Lee H, Lee Y. Visualization of Document Retrieval Using External Cluster Relationship [J]. Journal of Information Science and Engineering, 2013, 29 (1): 35-48.
[13] 任永功. 面向聚类的数据可视化方法及相关技术研究[D]. 沈阳: 东北大学, 2006. (Ren Yonggong. Study on Data Visualization Methods and Related Techniques for Clustering[D]. Shenyang: Northeastern University, 2006.)
[14] 薛浩, 马静, 朱恒民, 等. 基于SOM聚类的文本挖掘知识展现可视化研究[J]. 情报理论与实践, 2009, 32(7): 120-123. (Xue Hao, Ma Jing, Zhu Hengmin, et al. Research on Knowledge Visualization of Text Mining Based on SOM Cluster [J]. Information Studies: Theory & Application, 2009, 32(7): 120-123.)
[15] 杨钤雯, 寇纪淞, 陈富赞, 等. 基于本体的语义网络会话聚类和可视化方法[J]. 模式识别与人工智能, 2011, 24(1): 111-116. (Yang Qianwen, Kou Jisong, Chen Fuzan, et al. Semantic Web Session Clustering and Visualization Method Based on Ontology [J]. Pattern Recognition and Artificial Intelligence, 2011, 24(1): 111-116.)
[16] 任永功, 于戈. 一种多维数据的聚类算法及其可视化研究[J]. 计算机学报, 2005, 28(11): 1861-1865. (Ren Yonggong, Yu Ge. Clustering for Multi-Dimensional Data and Its Visualization[J]. Chinese Journal of Computers, 2005, 28(11): 1861-1865.)
[17] Krishman M, Bohn S, Cowley W, et al. Scalable Visual Analytics of Massive Textual Datasets [C]. In: Proceedings of the 21st International Parallel and Distributed Processing Symposium, Long Beach, CA, US. IEEE, 2007: 26-30.
[18] 王伟. 基于网络信息的热点事件发现与分析研究——以创业板上市公司为例[D]. 上海: 华东师范大学, 2011. (Wang Wei. Hot Event Detection and Analysis Based on Internet Information - Case Studies on GEM Listed Companies [D]. Shanghai: East China Normal University, 2011.)
[19] Tirunagari S, Hänninen M, Stählberg K, et al. Mining Causal Relations and Concepts in Maritime Accidents Investigation Reports[C]. In: Proceedings of International Conference cum Exhibition on Technology of the Sea, Visakhapatnam, India. 2012: 548-566.
[20] 赵琦, 张智雄, 孙坦, 等. 主题发现技术方法研究[J]. 情报理论与实践, 2009, 32(4): 104-108. (Zhao Qi, Zhang Zhixiong, Sun Tan, et al. Study on Topic Discovery Technology [J]. Information Studies: Theory & Application, 2009, 32(4): 104-108.)
[21] 王小华, 徐宁, 谌志群. 基于共词分析的文本主题词聚类与主题发现[J]. 情报科学, 2011, 29 (11): 1621-1624. (Wang Xiaohua, Xu Ning, Chen Zhiqun. Discovering of Subjects and Clustering of Textual Subject Terms Based on Co-word Analysis[J]. Information Science, 2011, 29(11): 1621-1624.)
[22] Fortuna B, Mladenic D, Crobelnik M. Semi-automatic Construction of Topic Ontologies [C]. In: Proceedings of the 2005 Joint International Conference on Semantics, Web and Mining (EWMF'05/KDO'05). Berlin, Heidelberg: Springer- Verlag, 2006: 121-131.
[23] 钟伟金, 李佳. 共词分析法研究(一)——共词分析的过程与方式[J]. 情报杂志, 2008 (5): 70-72. (Zhong Weijin, Li Jia. The Research of Co-word Analysis (1) - the Process and Methods of Co-word Analysis [J]. Journal of Information, 2008 (5): 70-72.)
[24] 马连浩. Web文本聚类技术及聚类结果可视化研究[D]. 大连: 大连交通大学, 2008. (Ma Lianhao. Research of Web Text Clustering Technology and Clustering Result Visualization [D]. Dalian: Dalian Jiaotong University, 2008.) |