Algorithm for Mining Repeated Sequential Patterns

Abstract

Mining sequential pattern is of having a significant role in many applications including study of sensor signals, analysis of a consumer behavior, weather forecasting, etc. In this the further study of sequential patterns, named by  time-interval sequential patterns, was proposed by Chen, Jiang, and Ko, which predicts the time intervals between  the consecutive items along with the order of items. For example: A customer buy will buy a printer in two months and then buy DVD writer in four months after he bought scanner. Even though these time-interval sequential patterns predict, when the same customer could buy the next item, these can’t predict when repeated item will be bought. Hence, here we are presenting an efficient algorithm, RT-Apriori to solve these types of problems. The experimental results also shows that RT -Apriori algorithm exhibiting better scalability.