Semi-Supervised clustering and Local Scale Learning algorithm

被引：0

作者：

Bchir, Ouiem ^{[1
]}

Frigui, Hichem ^{[2
]}

Ben Ismail, Mohamed Maher ^{[1
]}

机构：

[1] King Saud Univ, Dept Comp Sci, Riyadh, Saudi Arabia

[2] Univ Louisville, Multimedia Res Lab, Louisville, KY USA

来源：

WORLD CONGRESS ON COMPUTER & INFORMATION TECHNOLOGY (WCCIT 2013) | 2013年

关键词：

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

We propose a new semi-supervised relational clustering approach, called Semi-Supervised relational clustering with local scaling parameter (SS-LSL). The proposed algorithm learns a cluster dependent Gaussian kernel while finding compact clusters. SS-LSL uses side-information in the form of a small set of constraints on which instances should or should not reside in the same cluster. The proposed algorithm uses only the pairwise relation between the feature vectors. This makes it applicable when similar objects cannot be represented by a single prototype. Using synthetic and real data sets, we show that SS-LSL outperforms several other algorithms.

引用

页数：5

共 50 条

[11] A SEMI-SUPERVISED ENSEMBLE LEARNING ALGORITHM
Jiang, Zhen
Zhang, Shiyong
[J]. 2012 IEEE 2ND INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND INTELLIGENT SYSTEMS (CCIS) VOLS 1-3, 2012, : 913 - 918
[12] Semi-supervised Clustering with Deep Metric Learning
Li, Xiaocui
Yin, Hongzhi
Zhou, Ke
Chen, Hongxu
Sadiq, Shazia
Zhou, Xiaofang
[J]. DATABASE SYSTEMS FOR ADVANCED APPLICATIONS, 2019, 11448 : 383 - 386
[13] Active Learning of Constraints for Semi-Supervised Clustering
Xiong, Sicheng
Azimi, Javad
Fern, Xiaoli Z.
[J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2014, 26 (01) : 43 - 54
[14] A semi-supervised clustering algorithm based on local scaling graph and label propagation
Hu, Jiani
[J]. 2011 INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND NETWORK TECHNOLOGY (ICCSNT), VOLS 1-4, 2012, : 1059 - 1062
[15] An Inductive Semi-supervised Learning Approach for the Local and Global Consistency Algorithm
de Sousa, Celso A. R.
[J]. 2016 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2016, : 4017 - 4024
[16] A semi-supervised multiview spectral clustering algorithm based on distance metric learning
Yang J.
Deng T.
[J]. Sichuan Daxue Xuebao (Gongcheng Kexue Ban)/Journal of Sichuan University (Engineering Science Edition), 2016, 48 (01): : 146 - 151
[17] Local homogeneous consistent safe semi-supervised clustering
Gan, Haitao
Fan, Yingle
Luo, Zhizeng
Zhang, Qizhong
[J]. EXPERT SYSTEMS WITH APPLICATIONS, 2018, 97 : 384 - 393
[18] Semi-supervised fuzzy clustering algorithm based on QPSO
School of IoT Engineering, Jiangnan University, Wuxi 214122, China
[J]. J. Inf. Comput. Sci., 1 (93-101):
[19] A Semi-supervised Clustering Algorithm Based on Rough Reduction
Lin, Liandong
Qu, Wei
Yu, Xiang
[J]. CCDC 2009: 21ST CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6, PROCEEDINGS, 2009, : 5427 - +
[20] A semi-supervised document clustering algorithm based on EM
Rigutini, L
Maggini, M
[J]. 2005 IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE, PROCEEDINGS, 2005, : 200 - 206

← 1 2 3 4 5 →