Our team(THUIR2) participated in both FOSS and POSS subtasks of the NTCIR-16. Session Search (SS) Task. This paper describes our approaches and results. In the FOSS subtask, we submit five runs by using a learning-to-rank model and a fine-tuned pre-trained language model. We fine-tune the pre-trained language model with both ad-hoc data and session information and then assembled them by a learning-to-rank method. The assembled model achieves the best performance among all participants in the preliminary evaluation. In the POSS subtask, we used an assembled model which also achieves the best performance in the preliminary evaluation.
Su et al. (Tue,) studied this question.