Mining association rules in interval-based temporal sequences - ZHU Tian1; BAI Shi-xue2; WANG Bai1; WU Bin1 (Tongxin xuebao, 2009)
A new algorithm was proposed to find association rules in interval-based sequences, which was based on the concept of interval time series and used the properties of frequent closed patterns. By the properties of frequent closed patterns, the algorithm can avoid generating the redundancy candidate sequences, thus decreases the time and space complexity and improves the efficiency of the algorithm.