Publication

Abstract : Rough set theory is a mathematical framework developed by Polish computer scientist Zdzislaw Pawlak in the early 1980s. It is a mathematical approach for dealing with uncertainty and vagueness in data. Rough set theory provides a formal method to analyze and extract knowledge for imprecise or incomplete data. Rough graphs are another approach to modeling these types of imprecise data in which it combines the concepts of graph theory in rough set domain. This emerging concept can be applied in social network analysis, biological networks and semantic graph analysis. Tong He introduced Rough graph in 2006 using set approximations. In this graph, objects are represented as vertices(nodes) and the relationship between objects are marked with edges. Rough graphs are specifically used in visualizing complex datasets and understanding the structure and patterns within the data. In this paper we have introduced labeling on rough graph using a similarity measure between vertices (vi, vj ). Also, we have calculated energy of a rough graph.