Abstract
Decision rule has been widely used for its briefness, effectiveness and favorite understandability. Many methods aiming at mining decision rules have been developed. Rough set theory. Unfortunately, data is split between multiple parties in many cases. And privacy concerns may prevent these parties from directly sharing the data. This paper addresses the problem of how to securely mine decision rules over horizontally partitioned data with rough set approach. This paper integrates a general framework rather than a very specific solution for mining decision rules with rough set approach when privacy is concerned and data is horizontally partitioned.
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Acknowledgements
This paper is supported by grants from National Key R&D Program of China (2016YFF0204205, 2017YFF0206503, 2017YFF0209004) and China National Institute of Standardization (712016Y-4941, 522016Y-4681, 522018Y-5948, 522018Y-5941, 522017Z-5853, 522017Z-5459).
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Wang, H., Zhao, J., Wu, G., Chao, Z., Fan, Z., Cao, X. (2019). Decision Rules Mining with Rough Set. In: Ahram, T. (eds) Advances in Artificial Intelligence, Software and Systems Engineering. AHFE 2018. Advances in Intelligent Systems and Computing, vol 787. Springer, Cham. https://doi.org/10.1007/978-3-319-94229-2_35
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DOI: https://doi.org/10.1007/978-3-319-94229-2_35
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