A rough set theory is a new mathematical tool to deal with uncertainty and vagueness of
decision system and it has been applied successfully in all the fields. It is used to identify the …

摘要在阐释粗糙集理论基本体系结构的基础上, 从多个角度探讨粗糙集模型的研究思路,
分析粗糙集理论与模糊集, 证据理论, 粒计算, 形式概念分析, 知识空间等其它理论之间的联系 …

This study provides a comprehensive overview of the publications in Information Sciences
(INS) from 1968 to 2016 inclusive, which encompasses the history of this journal from its …

We propose a framework for the study of covering based rough set approximations. Three
equivalent formulations of the classical rough sets are examined by using equivalence …

Feature subset selection is viewed as an important preprocessing step for pattern
recognition, machine learning and data mining. Most of researches are focused on dealing …

Recommender systems attempt to guide users in decisions related to choosing items based
on inferences about their personal opinions. Most existing systems implicitly assume the …

In this paper, we contribute to a recent and successful modelization of uncertainty, which the
practitioner often encounters in the formulation of multicriteria group decision making …

Rough sets, a tool for data mining, deal with the vagueness and granularity in information
systems. This paper studies covering-based rough sets from the topological view. We …

By introducing the new concepts of fuzzy β-covering and fuzzy β-neighborhood, we define
two new types of fuzzy covering rough set models which can be regarded as bridges linking …

Granular computing and knowledge reduction are two basic issues in knowledge
representation and data mining. Granular structure of concept lattices with application in …