Mining High Utility Temporal Patterns on Time Interval-Based Data

In this paper, we propose a novel temporal pattern mining problem, named high utility temporal pattern mining, to fulfill the needs of various applications. Different from classical temporal pattern mining aiming at discovering frequent temporal patterns, high utility temporal pattern mining is to find each temporal pattern whose utility is greater than or equal to the minimum utility threshold. To facilitate efficient high utility temporal pattern mining, several extension and pruning strategies are proposed to reduce the search space. HUTPMiner algorithm is then proposed to efficiently mine high utility temporal patterns with the aid of the proposed extension and pruning strategies. Experimental results show that HUTPMiner algorithm is able to prune a lot of candidates, thereby achieving high mining efficiency.