Mining the future: Predicting itemsets' support of association rules mining

This paper proposes a novel research dimension in the field of data mining, which is mining the future data before its arrival, or in other words: predicting association rules ahead before the arrival of the data. To achieve that, we need only predict the itemsets' support, upon which association rules could be easily produced. A time series analysis approach (MFTP) is proposed to perform itemsets' support prediction task. The proposed technique outperforms other prediction techniques for short history. The conducted performance study showed good prediction accuracy and response time. Thus, we provide a new tool to provide more information in the decision support field.