Journal
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
Volume 25, Issue 2, Pages 274-284Publisher
IEEE COMPUTER SOC
DOI: 10.1109/TKDE.2011.220
Keywords
Variable precision rough-set model; knowledge discovery; granular computing; information systems; incremental updating
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Funding
- National Science Foundation of China [60873108, 61175047, 61100117]
- Fundamental Research Funds for the Central Universities [SWJTU11ZT08]
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Approximations of a concept by a variable precision rough-set model (VPRS) usually vary under a dynamic information system environment. It is thus effective to carry out incremental updating approximations by utilizing previous data structures. This paper focuses on a new incremental method for updating approximations of VPRS while objects in the information system dynamically alter. It discusses properties of information granulation and approximations under the dynamic environment while objects in the universe evolve over time. The variation of an attribute's domain is also considered to perform incremental updating for approximations under VPRS. Finally, an extensive experimental evaluation validates the efficiency of the proposed method for dynamic maintenance of VPRS approximations.
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