Accepted Papers

  • An Interpretable Method in Association Rule Mining For Strategic Decision Making About Household Size Control Utilizing Rough Set Theory
    Ali Abbas Abadi1 and Marziyeh Bahrami2,Mohammad Esmaeili2, 1Department of Computer Engineering, South Tehran Branch, Islamic Azad university, Tehran, Iran, 2Department of Computer Engineering, Ardabil Sience and Reasearch Branch, Islamic Azad University, Ardabil, Iran

    Considerable growth of Information Technology makes it a milestone in the strategic decision-making. Population control for the aim of resource productivity, balancing labor force as well as developing macroeconomic policies of a country is a must. Handling these challenges requires both analyzing the previous years’ data and its uncertainty as well as missing values. Analyzing the previous and ongoing researches shows that the problem of controlling population, despite its importance, is lessconsidered by the data mining experts. This study aims at considering this important issue by proposing a comparative framework to handle indistinguishable data items by using the rough set theory also evaluating foremost algorithms for the state of the pre-processing, feature extraction and exploration of association rules algorithms in a case study of demographic data provided by Iran Statistics Center (ISC). It was observed in the course of experiments that obtained results not only have the capability of being operational in strategic decision-making at the macroeconomic policies level, but also are useful for analysis of other demographic data.