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http://hdl.handle.net/1942/14779
Title: | A Rough-Set-Based Incremental Approach for Updating Approximations under Dynamic Maintenance Environments | Authors: | Chen, Hongmei Li, Tianrui RUAN, Da Lin, Jianhui Hu, Chengxiang |
Issue Date: | 2013 | Publisher: | IEEE COMPUTER SOC | Source: | IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 25 (2), p. 274-284 | Abstract: | 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. | Notes: | Li, TR (reprint author), [Chen, Hongmei; Li, Tianrui] SW Jiaotong Univ, Sch Informat Sci & Technol, Chengdu 610031, Peoples R China. [Ruan, Da] Univ Ghent, Dept Appl Math & Comp Sci, Ghent, Belgium. [Ruan, Da] Hasselt Univ, Dept Appl Econ, Diepenbeek, Belgium. [Ruan, Da] Univ Technol Sydney, Fac Informat Technol, Sydney, NSW 2007, Australia. [Lin, Jianhui] SW Jiaotong Univ, Tract Power State Key Lab, Chengdu 610031, Peoples R China. [Hu, Chengxiang] Chuzhou Univ, Sch Comp & Informat Engn, Chuzhou 239000, Peoples R China. hmchen@swjtu.edu.cn; trli@swjtu.edu.cn; linjhyz@126.com; chengxiang0550@163.com | Keywords: | Variable precision rough-set model; knowledge discovery; granular computing; information systems; incremental updating;Computer Science, Artificial Intelligence; Computer Science, Information Systems; Engineering, Electrical & Electronic; Variable precision rough-set model; knowledge discovery; granular computing; information systems; incremental updating | Document URI: | http://hdl.handle.net/1942/14779 | ISSN: | 1041-4347 | e-ISSN: | 1558-2191 | DOI: | 10.1109/TKDE.2011.220 | ISI #: | 000314188900005 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2014 |
Appears in Collections: | Research publications |
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