Information Cartography in Association Rule Mining

Association Rule Mining is a machine learning method for discovering the interesting relations between attributes in huge transaction database. Typically, algorithms generate number of association rules, from which it hard to extract structured knowledge and present this automatically form that would be suitable user. Recently, an information cartography has been proposed creating summaries visualizing with methodology called “metro maps”. This was applied several problem domains, where pattern mining necessary. The aim study develop automatic creation metro maps obtained by and, thus, spread its applicability other methods. Although consists multiple steps, core presents map construction defined as optimization problem, solved using evolutionary algorithm. Finally, four well-known UCI Machine Learning datasets one sport dataset. Visualizing resulted not only justifies tool presenting hidden data, but also they can tell stories users.