Abstract Most existing heterogeneous information network (HIN) embedding methods focus on static environments while neglecting the evolving characteristic of real-world networks. Although several dynamic have been proposed, they are merely designed for homogeneous networks and cannot be directly applied in environments. To tackle above challenges, we propose a novel framework incorporating temp...