[1] BASU S, BANERJEE A, MOONEY R J. Semi-supervised clustering by seeding[C]//Proceedings of the 19th International Conference on Machine Learning. San Francisco, CA:Morgan Kaufmann Publishers, 2002:27-34. [2] WAGSTAFF K, CARDIE C. Clustering with instance-level constraints[C]//Proceedings of the 17th International Conference on Machine Learning, San Francisco, CA:Morgan Kaufmann Publishers, 2000:1103-1110. [3] 王玲, 薄列峰, 焦李成. 密度敏感的半监督谱聚类[J]. 软件学报, 2007, 18(10):2412-2422.(WANG L, BO L F, JIAO L C. Density-sensitive semi-supervised spectral clustering[J]. Journal of Software, 2007, 18(10):2412-2422.) [4] 肖宇,于剑. 基于近邻传播算法的半监督聚类[J]. 软件学报, 2008, 19(11):2803-2813.(XIAO Y, YU J. Semi-supervised clustering based on affinity propagation algorithm[J]. Journal of Software, 2008, 19(11):2803-2813.) [5] 尹学松, 胡思良, 陈松灿. 基于成对约束的判别型半监督聚类分析[J]. 软件学报, 2008, 19(11):2791-2802.(YIN X S, HU S L, CHEN S C. Discriminative semi-supervised clustering analysis with pairwise constraints[J]. Journal of Software, 2008, 19(11):2791-2802.) [6] BASU S, BANERJEE A, MOONEY R J. Active semi-supervision for pairwise constrained clustering[EB/OL].[2018-03-20]. https://www.semanticscholar.org/paper/Active-Semi-Supervision-for-Pairwise-Constrained-Basu-Banerjee/114e5f6f1910dafa0468e998 a78f0d268de9c02e/pdf. [7] 李晁铭, 徐圣兵, 郝志峰. 基于成对约束的交叉熵半监督聚类算法[J]. 模式识别与人工智能, 2017, 30(7):598-608.(LI C M, XU S B, HAO Z F. Cross-entropy semi-supervised clustering based on pairwise constraints[J]. Pattern Recognition and Artificial Intelligence, 2017, 30(7):598-608.) [8] 王纵虎, 刘速. 一种成对约束限制的半监督文本聚类算法[J]. 计算机科学, 2016, 43(12):183-188.(WANG Z H, LIU S. Pairwise constrained semi-supervised text clustering algorithm[J]. Computer Science, 2016, 43(12):183-188.) [9] BASU S, BILENKO M, MOONEY R J. A probabilistic framework for semi-supervised clustering[C]//Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York:ACM, 2004:59-68. [10] XIONG S, AZIMI J, FERN X Z. Active learning of constraints for semi-supervised clustering[J]. IEEE Transactions on Knowledge & Data Engineering, 2014, 26(1):43-54. [11] RODRIGUEZ A, LAIO A. Clustering by fast search and find of density peaks[J]. Science, 2014, 344(6191):1492. [12] ASUNCION A,NEWMAN D.UCI machine learning repository[EB/OL].[2014-02-18].http://www.ics.uci.edu/~mlearn/MLRepository.html. [13] WU M,SCHOLKOPF B.A local learning approach for clustering[C]//Proceedings of the the 19th International Conference on Neural Information Processing Systems. Cambridge, MA:MIT Press,2006:1529-1536. |