Abstract: As there are number of Data mining algorithms have been proposed in previous years, but it is tough to define comprehensive study to compare these algorithms. k-means algorithm is the first algorithm proposed in this field. With respect to time number of changes proposed in k-means to enhance the performance in term of time. This paper proposes an innovative utility sentient approach for the mining of interesting association patterns from OLAP database. This algorithm uses the results of this analysis to define the parameters of the mining model. While you can use different algorithms to perform the same business task, each algorithm produces a different result, and some algorithms can produce more than one type of result.
Keywords: k-means Rules, rule mining algorithms, minimum support, computation power, frequent Items