In this paper, we present the system and results of The STIS team for the Information Retrieval (English) subtasks of the NTCIR-16 Data Search Task. The data collections in this task consist of a pair of metadata and a set of data files. We only used title, description, and tags of metadata as input documents of our proposed approach to retrieve a rank of query-related data files. We proposed using a pre-trained model to capture representative words prediction for each document then calculate the similarity between the query and the representative words as a rank score.
Suadaa et al. (Tue,) studied this question.