[1]邓思宇,刘福伦,黄雨婷,等.基于PageRank的主动学习算法[J].智能系统学报,2019,14(3):551-559.[doi:10.11992/tis.201804052]
 DENG Siyu,LIU Fulun,HUANG Yuting,et al.Active learning through PageRank[J].CAAI Transactions on Intelligent Systems,2019,14(3):551-559.[doi:10.11992/tis.201804052]
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基于PageRank的主动学习算法

参考文献/References:
[1] MINN S, 傅顺开, 吕天依, 等. 一般贝叶斯网络分类器及其学习算法[J]. 计算机应用研究, 2016, 33(5):1327-1334 MINN S, FU Shunkai, LV Tianyi, et al. Algorithm for exact recovery of Bayesian network for classification[J]. Application research of computer, 2016, 33(5):1327-1334
[2] 王翔, 胡学钢, 杨秋洁. 基于One-R的改进随机森林入侵检测模型研究[J]. 合肥工业大学学报(自然科学版), 2015, 38(5):627-630, 711 WANG Xiang, HU Xuegang, YANG Qiujie. Research on improved intrusion detection model with random forest based on feature evaluation of One-R[J]. Journal of Hefei University of Technology (natural science), 2015, 38(5):627-630, 711
[3] YANG Yi, CHEN Wenguang. Taiga:performance optimization of the C4.5 decision tree construction algorithm[J]. Tsinghua science and technology, 2016, 21(4):415-425.
[4] ZHOU Xueyuan, BELKIN M. Semi-supervised learning[J]//Journal of the royal statistical society, 2010, 172(2):530.
[5] WANG Min, MIN Fan, ZHANG Zhiheng, et al. Active learning through density clustering[J]. Expert systems with applications, 2017, 85:305-317.
[6] 胡小娟, 刘磊, 邱宁佳. 基于主动学习和否定选择的垃圾邮件分类算法[J]. 电子学报, 2018, 46(1):203-209 HU Xiaojuan, LIU Lei, QIU Ningjia. A novel spam categorization algorithm based on active learning method and negative selection algorithm[J]. Acta electronica sinica, 2018, 46(1):203-209
[7] SYED A R, ROSENBERG A, KISLAL E. Supervised and unsupervised active learning for automatic speech recognition of low-resource languages[C]//Proceedings of 2016 IEEE International Conference on Acoustics, Speech and Signal Processing. Shanghai, China, 2016:5320-5324.
[8] SUN Shujin, ZHONG Ping, XIAO H, et al. An MRF model-based active learning framework for the spectral-spatial classification of hyperspectral imagery[J]. IEEE journal of selected topics in signal processing, 2015, 9(6):1074-1088.
[9] YANG Yi, MA Zhigang, NIE Feiping, et al. Multi-class active learning by uncertainty sampling with diversity maximization[J]. International journal of computer vision, 2015, 113(2):113-127.
[10] XIONG Sicheng, AZIMI J, FERN X Z. Active learning of constraints for semi-supervised clustering[J]. IEEE transactions on knowledge and data engineering, 2014, 26(1):43-54.
[11] BLOODGOOD M. Support vector machine active learning algorithms with query-by-committee versus closest-to-hyperplane selection[C]//Proceedings of 2018 IEEE 12th International Conference on Semantic Computing. Laguna Hills, USA, 2018:148-155.
[12] BRIN SERGEY, PAGE Lawrence. The anatomy of a large-scale hypertextual web search engine[J]. Computer networks and ISDN systems, 1998, 30(1/7):107-117.
[13] DENG Zhenyun, ZHU Xiaoshu, CHENG Debo, et al. Efficient kNN classification algorithm for big data[J]. Neurocomputing, 2016, 195:143-148.
[14] GILAD-BACHRACH R, NAVOT A, TISHBY N. Kernel query by committee (KQBC)[R]. Technical Report 2003-88, Leibniz Center, the Hebrew University, 2003.
[15] CAI Deng, HE Xiaofei. Manifold adaptive experimental design for text categorization[J]. IEEE transactions on knowledge and data engineering, 2012, 24(4):707-719.
[16] MIN Fan, ZHU W. A competition strategy to cost-sensitive decision trees[C]//Proceedings of the 7th International Conference on Rough Sets and Knowledge Technology. Chengdu, China, 2012:359-368.
[17] 张桃, 吴小伟. 基于PageRank的马尔可夫链研究[J]. 电子设计工程, 2017, 25(9):36-38 ZHANG Tao, WU Xiaowei. The study of Markov chains based on PageRank[J]. Electronic design engineering, 2017, 25(9):36-38
[18] LIU Dun, LI Tianrui, LIANG Decui. Incorporating logistic regression to decision-theoretic rough sets for classifications[J]. International journal of approximate reasoning, 2014, 55(1):197-210.
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备注/Memo

收稿日期:2018-04-26。
基金项目:国家自然科学基金项目(61379089).
作者简介:邓思宇,女,1993年生,硕士研究生,主要研究方向为代价敏感学习、主动学习;刘福伦,男,1993年生,硕士研究生,主要研究方向为代价敏感学习、粗糙集、主动学习;黄雨婷,女,1996年生,主要研究方向为推荐系统。
通讯作者:汪敏.E-mail:wangmin80616@163.com

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