Multi-Task Multi-View Clustering for Non-Negative Data

Multi-task clustering and multi-view clustering have severally found wide applications and received much attention in recent years. Nevertheless, there are many clustering problems that involve both multi-task clustering and multi-view clustering, i. e. , the tasks are closely related and each task can be analyzed from multiple views. In this paper, for non-negative data (e. g. , documents), we introduce a multi-task multi-view clustering (MTMVC) framework which integrates withinview-task clustering, multi-view relationship learning and multi-task relationship learning. We then propose a specific algorithm to optimize the MT- MVC framework. Experimental results show the superiority of the proposed algorithm over either multi-task clustering algorithms or multi-view clustering algorithms for multi-task clustering of multiview data.

Authors

• Xianchao Zhang Dalian University of Technology
• Xiaotong Zhang
• Han Liu ShenZhen University

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