JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2018, Vol. 53 ›› Issue (8): 9-16.doi: 10.6040/j.issn.1671-9352.4.2018.100

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Attribute reduction of incomplete contexts based on similarity relations

LI Tong-jun1,2, HUANG Jia-wen, WU Wei-zhi1,2   

  1. 1. Key Laboratory of Oceanographic Big Data Mining &
    Application of Zhejiang Province, Zhejiang Ocean University, Zhoushan 316022, Zhejiang, China;
    2. School of Mathematics, Physics and Information Science, Zhejiang Ocean University, Zhoushan 316022, Zhejiang, China
  • Received:2018-04-15 Online:2018-08-20 Published:2018-07-11

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Abstract: The paper focuses on the attribute reduction of incomplete contexts. First, by comparing the values of the objects on each of the attributes, one kind of similarity relations is proposed in incomplete contexts, based on which decision rules with clear meaning can be revealed via rough approximation operators. Subsequently, one type of attribute reduction of incomplete contexts is defined, under which the similarity relations keep unchanged, some judgment theorems are given for attribute reduction, and different types of attributes for attribute reduction are characterized by the similarity relations. At last, by constructing a Boolean function with discernibility attributes among objects, an approach for attribute reduction is obtained, and an illustration example is taken to show the reliability of approach.

Key words: incomplete contexts, rough sets, discernibility attributes, attribute reduction

CLC Number: 

  • TP18
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