A Concept of Multi Rough Sets defined on Multi-Contextual Information Systems

Rolly Intan
Petra Christian University
Department of Informatics Engineering
Surabaya, Indonesia
Corresponding E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.


Rough set theory, introduced by Pawlak in 1982[12], is an important concept in constructing many applications of Data Mining and Knowledge Discovery. Rough set as a gen-eralization of crisp set, deals with crisp granularity of objects by providing an alternative to for-mulate a given crisp set with imprecise boundaries. In rough set theory, a given crisp set of object is approximated into two different subsets derived from a crisp partition defined on the universal set of objects. The universal set of objects is characterized by a non-empty finite set of attributes, called data table or information system. The information system is formally represent-ed by a pair (U, A) in which U is a universal set of objects and A is a finite set of attributes. In the real application, depending on the context, a given object may have different values of at-tributes. Thus, a given set of objects might be approximated based on multi-context of attributes, called multi-contextual information systems. Here, n context of attributes will provide n partitions. Clearly, a given set of object, X⊆U, may then be represented by n pairs of lower and upper approximations. The n pairs of lower and upper approximations are denoted as multi rough sets of X as already proposed in [5,6]. This paper extends the concept of multi rough sets by providing more properties and examining more set operations.

Keywords: rough sets, multi rough sets, granular computing, multi-context of attributes.


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