Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/108604
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Type: | Conference paper |
Title: | Incremental attribute reduction in incomplete decision systems |
Author: | Shu, W. Shen, H. |
Citation: | Proceedings - International Symposium on Parallel Architectures, Algorithms and Programming, PAAP, 2012, pp.250-254 |
Publisher: | IEEE |
Publisher Place: | Online |
Issue Date: | 2012 |
ISBN: | 9780769548982 |
ISSN: | 2168-3034 2168-3042 |
Conference Name: | Fifth International Symposium on Parallel Architectures, Algorithms and Programming (PAAP) (17 Dec 2012 - 20 Dec 2012 : Tapei, Taiwan) |
Statement of Responsibility: | Wenhao Shu, Hong Shen |
Abstract: | According to whether the underlying information decision system varies with time, methods for attribute reduction can be categoried as static and dynamic two groups. While most existing work is done for the former, seveval approaches have been developed recently for the latter if the information system is complete, i.e. contains no missing values on any attribute. As to dynamic attribute reduction in incomplete decision systems, there is no work known to our knowledge. In this paper, with the introduction of lower approximation attribute reduction into incomplete decision systems, we present an incremental attribute reduction updating scheme based on discernibility matrices when object set is added to an incomplete decision system. |
Keywords: | Incremental attribute reduction; rough set theory; incomplete decision systems; discernibility matrix; positive region |
Rights: | © 2012 IEEE |
DOI: | 10.1109/PAAP.2012.42 |
Published version: | http://dx.doi.org/10.1109/paap.2012.42 |
Appears in Collections: | Aurora harvest 3 Computer Science publications |
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RA_hdl_108604.pdf Restricted Access | Restricted Access | 165.46 kB | Adobe PDF | View/Open |
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