[1]NIE Fei,GAO Yanli,DENG Zhaohong,et al.Possibility-matching based knowledge transfer prototype clustering algorithm[J].CAAI Transactions on Intelligent Systems,2020,15(5):978-989.[doi:10.11992/tis.201810028]
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Possibility-matching based knowledge transfer prototype clustering algorithm

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 15 Number of periods: 2020 5 Page number: 978-989 Column: 学术论文—知识工程 Public date: 2020-09-05
Title:
Possibility-matching based knowledge transfer prototype clustering algorithm
Author(s):
NIE Fei1;  GAO Yanli2;  DENG Zhaohong1;  WANG Shitong1
1. School of Digital Media, Jiangnan University, Wuxi 214122, China;
2. Jiangnan Institute of Computing Technology, Wuxi 214083, China
Keywords:
transfer prototype clustering; transfer learning mechanism; mandatory matching; possibility matching; prototype clustering; adjustability
CLC:
TP181
DOI:
10.11992/tis.201810028
Abstract:
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References:
[1] PAN S J, YANG Qiang. A survey on transfer learning[J]. IEEE transactions on knowledge and data engineering, 2010, 22(10): 1345-1359.
[2] TAO Jianwen, CHUNG F L, WANG Shitong. On minimum distribution discrepancy support vector machine for domain adaptation[J]. Pattern recognition, 2012, 45(11): 3962-3984.
[3] SUN Zhuo, CHEN Yiqiang, QI Juan, et al. Adaptive localization through transfer learning in indoor Wi-Fi environment[C]//Proceedings of the 7th International Conference on Machine Learning and Applications. San Diego, CA, USA: IEEE, 2008: 331-336.
[4] BICKEL S, BRüCKNER M, SCHEFFER T. Discriminative learning for differing training and test distributions[C]//Proceedings of the 24th International Conference on Machine Learning. Corvalis, Oregon, USA: ACM, 2007: 81-88.
[5] LAWRENCE N D, PLATT J C. Learning to learn with the informative vector machine[C]//Proceedings of the 21st International Conference on Machine Learning. Banff, Alberta, Canada: ACM, 2004: 65.
[6] GAO Jing, FAN Wei, JIANG Jing, et al. Knowledge transfer via multiple model local structure mapping[C]//Proceedings of the 14th ACMKDD International Conference on Knowledge Discovery and Data Mining. Las Vegas, NV, United States: ACM, 2008: 283-291.
[7] MIHALKOVA L, MOONEY R J. Transfer learning by mapping with minimal target data[C]//Proceedings Association for the Advancement of Artificial Intelligence AAAI’08) Workshop Transfer Learning for Complex Tasks. Chicago: AAAI, 2008.
[8] DAVIS J, DOMINGOS P. Deep transfer via second-order Markov logic[C]//Proceedings of the 26th Annual International Conference on Machine Learning. Montreal, Quebec, Canada: ACM, 2009: 217-224.
[9] PAN S J, TSANG I W, KWOK J T, et al. Domain adaptation via transfer component analysis[J]. IEEE transactions on neural networks, 2011, 22(2): 199-210.
[10] WANG Zheng, SONG Yangqiu, ZHANG Changshui. Transferred dimensionality reduction[C]//European Conference on Machine Learning and Knowledge Discovery in Databases. Antwerp, Belgium: Springer, 2008: 550-565.
[11] YANG Pei, TAN Qi, DING Yehua. Bayesian task-level transfer learning for non-linear regression[C]//Proceedings of 2008 International Conference on Computer Science and Software Engineering. Hubei, China: IEEE, 2008: 62-65.
[12] BORZEMSKI L, STARCZEWSKI G. Application of transfer regression to TCP throughput prediction[C]//Proceedings of the 1st Asian Conference on Intelligent Information and Database Systems. Dong Hoi, Vietnam: IEEE, 2009: 28-33.
[13] LIU Junfa, CHEN Yiqiang, ZHANG Yadong. Transfer regression model for indoor 3D location estimation[C]//Proceedings of the 16th International Multimedia Modeling Conference on Advances in Multimedia Modeling. Chongqing, China: Springer, 2010: 603-613.
[14] DENG Zhaohong, JIANG Yizhang, CHOI K S, et al. Knowledge-leverage-based TSK Fuzzy System modeling[J]. IEEE transactions on neural networks and learning systems, 2013, 24(8): 1200-1212.
[15] DENG Zhaohong, JIANG Yizhang, CHUNG F L, et al. Knowledge-leverage-based fuzzy system and its modeling[J]. IEEE transactions on fuzzy systems, 2013, 21(4): 597-609.
[16] DAI Wenyuan, YANG Qiang, XUE Guirong, et al. Self-taught clustering[C]//Proceedings of the 25th International Conference on Machine Learning. Helsinki, Finland: ACM, 2008: 200-207.
[17] JIANG Wenhao, CHUNG F L. Transfer spectral clustering[C]//European Conference on Machine Learning and Knowledge Discovery in Databases. Bristol, UK: Springer, 2012: 789-803.
[18] HARTIGAN J A, WONG M A. Algorithm AS 136: a K-means clustering algorithm[J]. Journal of the royal statistical society. series C, 1979, 28(1): 100-108.
[19] 陈黎飞, 姜青山, 王声瑞. 基于层次划分的最佳聚类数确定方法[J]. 软件学报, 2008, 19(1): 62-72
CHEN Lifei, JIANG Qingshan, WANG Shengrui. A hierarchical method for determining the number of clusters[J]. Journal of software, 2008, 19(1): 62-72
[20] VURAL V, DY J G. A hierarchical method for multi-class support vector machines[C]//Proceedings of the 21st International Conference on Machine Learning. Banff, Alberta, Canada: ACM, 2004: 105.
[21] ZHAO Yanchang, SONG Junde. GDILC: a grid-based density-isoline clustering algorithm[C]//Proceedings of 2001 International Conferences on Info-Tech and Info-Net. Beijing, China: IEEE, 2001: 140-145.
[22] MA W M, CHOW T W S. A new shifting grid clustering algorithm[J]. Pattern recognition, 2004, 37(3): 503-514.
[23] TSAI C F, TSAI C W, WU Hanchang, et al. ACODF: a novel data clustering approach for data mining in large databases[J]. Journal of systems and software, 2004, 73(1): 133-145.
[24] 杭文龙, 蒋亦樟, 刘解放, 等. 迁移近邻传播聚类算法[J]. 软件学报, 2016, 27(11): 2796-2813
HANG Wenlong, JIANG Yizhang, LIU Jiefang, et al. Transfer affinity propagation clustering algorithm[J]. Journal of software, 2016, 27(11): 2796-2813
[25] DENG Zhaohong, JIANG Yizhang, CHUNG F L, et al. Transfer prototype-based fuzzy clustering[J]. IEEE transactions on fuzzy systems, 2016, 24(5): 1210-1232.
[26] HUANG J Z, NG M K, RONG Hongqiang, et al. Automated variable weighting in k-means type clustering[J]. IEEE transactions on pattern analysis and machine intelligence, 2005, 27(5): 657-668.
[27] GAN G, WU J. A convergence theorem for the fuzzy subspace clustering (FSC) algorithm[J]. Pattern recognition, 2008, 41(6): 1939-1947.
[28] KRISHNAPURAM R, KELLER J M. The possibilistic C-means algorithm: insights and recommendations[J]. IEEE transactions on fuzzy systems, 1996, 4(3): 385-393.
[29] BEZDEK J C. Pattern recognition with fuzzy objective function algorithms[M]. New York: Plenum Press, 1981.
[30] DAI Wenyuan, XUE Guirong, YANG Qiang, et al. Co-clustering based classification for out-of-domain documents[C]//Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. San Jose, California, USA: ACM, 2007: 210-219.
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