硕士生导师
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学历：博士研究生毕业
学位：工学博士学位
办公地点：犀浦3号教学楼31529
毕业院校：四川大学
学科：电子信息. 软件工程. 计算机应用技术
所在单位：计算机与人工智能学院
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Constraint Co-projections for Semi-supervised Co-clustering
影响因子：19.118
DOI码：10.1109/TCYB.2015.2496174
所属单位：西南交通大学
发表刊物：IEEE Transactions on Cybernetics
刊物所在地：UNITED STATES
关键字：Constraint co-projections, pairwise constraints, semi-supervised co-clustering
摘要：Co-clustering aims to simultaneously cluster the objects and features to explore intercorrelated patterns. However, it is usually difficult to obtain good co-clustering results by just analyzing the object-feature correlation data due to the sparsity of the data and the noise. Meanwhile, most co-clustering algorithms cannot take the prior information into consideration and may produce unmeaningful results. Semi-supervised co-clustering aims to incorporate the known prior knowledge into the co-clustering algorithm. In this paper, a new technique named constraint co-projections for semi-supervised co-clustering (CPSSCC) is presented. Constraint co-projections can not only make use of two popular techniques including pairwise constraints and constraint projections, but also simultaneously perform the object constraint projections and feature constraint projections. The two popular techniques are illustrated for semi-supervised co-clustering when some objects and features are believed to be in the same cluster a priori. Furthermore, we also prove that the co-clustering problem can be formulated as a typical eigen-problem and can be efficiently solved with the selected eigenvectors. To the best of our knowledge, constraint co-projections is first stated in this paper and this is the first work on using CPSSCC. Extensive experiments on benchmark data sets demonstrate the effectiveness of the proposed method. This paper also shows that CPSSCC has some favorable features compared with previous related co-clustering algorithms.
合写作者：Hongjun Wang, Tao Li, Yan Yang,李天瑞
第一作者：Shudong Huang
论文类型：学术论文
论文编号：20154701588392
学科门类：工学
一级学科：计算机科学与技术
卷号：Volume: 46
期号：Issue: 12, December 2016
页面范围：3047 - 3058
ISSN号：2168-2275
是否译文：否
发表时间：2015-11-13