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Synthesizing decision rules from multiple information sources: a neighborhood granulation viewpoint

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Abstract

In the big data era, data are usually described by multiple information sources in many practical application fields, and it is infeasible way to mine interesting knowledge from a centralized huge source directly after aggregating all information sources, due to the problems of massive data, privacy concerns, and potential transmission cost. To mine decision rules from multiple information sources, therefore, we can mine local decision rules at different local information sources, and then put these rules to form a set of global decision rules. In this paper, we first present a formal representation of decision rule, which depends on the neighborhood granulation of each sample from the viewpoint of granular computing. Then, we obtain the weight of each local information source based on the consensus measure principle between local information sources. Finally, a weighting model for mining global decision rules via synthesizing all local decision rules is proposed. Extensive experimental results demonstrate that the proposed decision rules synthesization model is effective and scalable.

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Acknowledgements

This work is supported by grants from the National Natural Science Foundation of China (Nos. 61672272, 61303131, and 61603173), the China Postdoctoral Science Foundation (2015M581298), the Program for New Century Excellent Talents in Fujian Province University, and the Natural Science Foundation of Fujian Province (Nos. 2016J01315, 2017J01507, and 2016J01314).

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Authors and Affiliations

  1. School of Computer Science, Minnan Normal University, Zhangzhou, 363000, People’s Republic of China

    Yaojin Lin, Huihuang Chen & Jinjin Li

  2. Key Laboratory of Data Science and Intelligence Application, Fujian Province University, Zhangzhou, 363000, People’s Republic of China

    Yaojin Lin & Huihuang Chen

  3. School of Mathematics and Statistics, Minnan Normal University, Zhangzhou, 363000, People’s Republic of China

    Guoping Lin, Jinkun Chen & Zhouming Ma

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  1. Yaojin Lin
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Correspondence to Yaojin Lin.

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Lin, Y., Chen, H., Lin, G. et al. Synthesizing decision rules from multiple information sources: a neighborhood granulation viewpoint. Int. J. Mach. Learn. & Cyber. 9, 1919–1928 (2018). https://doi.org/10.1007/s13042-018-0791-z

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  • DOI: https://doi.org/10.1007/s13042-018-0791-z

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