Rough Concept Analysis for Rough Classification

Nowadays, we need much time and effort for extracting useful information in a flood of data, which are generated everyday by the development of a computer. In order to solve such a problem, many approaches are proposed. Data Mining is the whole process for knowledge discovery by analyzing data, or by extracting patterns in specific categories from data. As a Data Mining approach, in recent days, interests in Formal Concept Analysis and Rough Set Theory are on the increase and researches based on them are going in progress actively. In this paper, we have proposed a rough concept analysis and developed Rough Concept Analyzer for rough classification and extract hidden knowledge easily from given vague data. Also we have demonstrated how our proposed approach can be applied in tag-based social bookmarking system through our experiment. By rough classification using the “Rough Concept Analyzer”, we can discover useful knowledge that cannot find out by using the FCA, from the vague data. Our tool would be helpful for rough classification and analyzing the uncertain data out of various fields. Key-Words: Rough Classification, Rough Concept Analysis, Roughness, Concept Lattice, Data Mining.