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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/52596

Title: Incremental fuzzy probabilistic rough sets over two universes
Authors: Jie Hu
Tianrui Li
Chuan Luo
Hamido Fujita
Shaoyong Li
Contributors: 國立臺灣海洋大學:資訊工程學系
Keywords: Rough sets
Two universes
Fuzzy relation
Approximations
Incremental updating
Date: 2017-02
Issue Date: 2019-11-22T02:48:11Z
Publisher: International Journal of Approximate Reasoning
Abstract: Abstract: The fuzzy Information System over Two Universes (ISTU) formalizing a data table corresponding to two universes as well as their relations is common in real-world applications, e.g., recommender system and clinical diagnosis system. The fuzzy probabilistic rough sets over two universes (FPRSMTU) can deal with a fuzzy relation and allow a tolerance inaccuracy in the construction of rough approximations in a fuzzy ISTU, which is a generalization of classic rough sets with fuzzy and probabilistic theories. As a necessary step for knowledge discovery based on rough sets, the fuzzy rough approximations of fuzzy ISTU need to be updated efficiently under dynamic data environment. Incremental technique is an efficient approach for dynamic information processing by making full use of previously obtained knowledge. In this paper, incremental approaches for updating approximations of fuzzy ISTU are proposed while some objects adding into or deleting from the two universes, and the corresponding incremental algorithms are designed. Experimental evaluations on real datasets as well as artificial datasets show the effectiveness of the proposed incremental updating method compared with the non-incremental method.
Relation: 81 pp.28-48
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/52596
Appears in Collections:[資訊工程學系] 期刊論文

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