Abstract
In this paper, computing attribute core for massive data based on rough set theory and MapReduce is studied, two novel algorithms for computing attribute core are proposed. A case study proves the correctness of the proposed algorithms, and the proposed algorithms are shown more efficient according to the experiment results on a real massive dataset.
Part of this work is supported by National Natural Science Foundation of China (No. 61075019), Scientific Research Foundation of Chongqing Municipal Education Commission (No. KJ110522, KJ110512), Natural Science Foundation of Chongqing University of Posts and Telecommunications(No. A2009-26, No. JK-Y-2010002).
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© 2012 Springer-Verlag Berlin Heidelberg
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Yang, Y., Chen, Z. (2012). Parallelized Computing of Attribute Core Based on Rough Set Theory and MapReduce. In: Li, T., et al. Rough Sets and Knowledge Technology. RSKT 2012. Lecture Notes in Computer Science(), vol 7414. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31900-6_20
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DOI: https://doi.org/10.1007/978-3-642-31900-6_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31899-3
Online ISBN: 978-3-642-31900-6
eBook Packages: Computer ScienceComputer Science (R0)