Ranking of association rules toward smart decision for smart city
Subrata Datta, Kalyani K Mali, Pratyay Roy · 2017
Ranking of association rules based on their significance in knowledge discovery has become an important issue in data mining. Traditional mining algorithms may often generate a huge number of rules including less or non-significant ones. Users expect is to deal with the most significant association rules to get a smart decision. Ranking express the level of significance which may reduce the confusion in decision making. This paper introduces Gravity as a measure of rule significance and henceforth ranks the association rules. Experimental analysis shows the effectiveness of the proposed technique.