Mining of high-utility itemsets in transactional databases is emerging topic in recent years since it can be used to reveal more information for decision making, which has been widely used in many real-life applications. For the traditional high-utility itemset mining (HUIM), only the utility values of the itemsets are considered without timestamps or periodic constraints. In this paper, we present a new short periodic high-utility itemset mining (SPHUIM) to mine the set of short periodic high-utility itemsets (SPHUIs) by considering both the period and utility measures. A baseline two-phase SPHUI-TP algorithm is first presented to mine SPHUIs in level-wise manner. To reduce the search space of SPHUI-TP algorithm, two pruning strategies are also developed to speed up the mining performance of the SPHUI-TP algorithm. Substantial experiments both on real-life and synthetic datasets showed the efficiency and effectiveness of the designed approaches.