Intelligent data mining systems by generalized multiple kernel machines on graph based subspace

研究成果: Conference contribution

摘要

Mining high-dimensional business data is a challenging problem. This paper proposes a novel approach to address the problems including (1) the curse of dimensionality and (2) the meaningfulness of the similarity measure in the high dimension space. The solution of this study is to build a generalized multiple kernel machine (GMKM) on a low-dimensional subspace. The representative subspace is created by the locally consistent matrix factorization (an improved variation of non-negative matrix factorization). The strengths of our system are two-fold: (1) GMKM takes products of kernels-corresponding to a tensor product of feature spaces. This leads to a richer and much higher dimensional feature representation, which is powerful in identifying relevant features and their apposite kernel representation. (2) Locally consistent matrix factorization finds a compact low-dimensional representation for data, which uncovers underlying information and simultaneously respects the intrinsic geometric structure of data manifold. Our system robustly outperforms traditional multiple kernel machines, and dimensionality reduction methods.

原文English
主出版物標題Proceedings of the 2015 7th IEEE International Conference on Cybernetics and Intelligent Systems, CIS 2015 and Robotics, Automation and Mechatronics, RAM 2015
發行者Institute of Electrical and Electronics Engineers Inc.
頁面120-125
頁數6
ISBN(電子)9781467373364
DOIs
出版狀態Published - 2015 九月 23
事件7th IEEE International Conference on Cybernetics and Intelligent Systems, CIS 2015 and the 7th IEEE International Conference on Robotics, Automation and Mechatronics, RAM 2015 - Siem Reap, Cambodia
持續時間: 2015 七月 152015 七月 17

出版系列

名字Proceedings of the 2015 7th IEEE International Conference on Cybernetics and Intelligent Systems, CIS 2015 and Robotics, Automation and Mechatronics, RAM 2015

Other

Other7th IEEE International Conference on Cybernetics and Intelligent Systems, CIS 2015 and the 7th IEEE International Conference on Robotics, Automation and Mechatronics, RAM 2015
國家Cambodia
城市Siem Reap
期間15-07-1515-07-17

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Control and Systems Engineering

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  • 引用此

    Huang, S. C., & Wu, T. K. (2015). Intelligent data mining systems by generalized multiple kernel machines on graph based subspace. 於 Proceedings of the 2015 7th IEEE International Conference on Cybernetics and Intelligent Systems, CIS 2015 and Robotics, Automation and Mechatronics, RAM 2015 (頁 120-125). [7274559] (Proceedings of the 2015 7th IEEE International Conference on Cybernetics and Intelligent Systems, CIS 2015 and Robotics, Automation and Mechatronics, RAM 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCIS.2015.7274559