Consumer Goods Quality and Safety Case Retrieval Based on Rough Sets

Abstract

This paper discusses the issue of consumer case retrieving from the perspective of establishing consumer products safety standards. To improve the searching efficiency in mass data, this paper puts forward rough sets theory to reduce consumer goods accident cases database. Specifically, discernibility matrix is employed to reduce the attributes of cases in order to find out key factors influencing quality and safety of customer goods. Then matching computation model is applied to retrieve and extract the data needed in the case database. The validity of this method can be verified by inputting the crucial factors we established into the practical projects that are carried out by the China Standardization Institute in terms of the research of consumer goods quality safety factors and standard building. Based on the discussion of this paper, the usage of rough sets aptly supports the case retrieval and reasoning, which provides reference for consumer goods quality safety warning model.