Before revision:  In this paper, we propose a pre-training and fine-tuning framework  PF-HIN  to capture the features of a HIN . Unlike traditional GNNs that have to train the whole model for each downstream task , PF-HIN only needs to fine-tune the model using the pre-trained parameters and minimal extra task-specific parameters, thus improving the model efficiency and effectiveness.
After revision:  In this paper, we propose a pre-training and fine-tuning framework PF-HIN to capture the features of a HIN . Unlike traditional network representation learning models that have to train the whole model for each downstream task , PF-HIN only needs to fine-tune the model using the pre-trained parameters and minimal extra task-specific parameters, thus improving the model efficiency and effectiveness.