In this paper, we report our work and discuss the results for NTCIR- 16 DataSearch-2 IR subtask. NTCIR-16 Data Search-2 was organized to improve the present knowledge and promote the concepts of dataset search among IR researchers. In this particular subtask, we tried to perform ad-hoc retrieval for datasets based on given queries. While this task was available in English and Japanese, we decided to only compete for the English subtask. We sought to perform the ranking of datasets by using traditional BM25-based ranking functions and recent language models. During the evaluation experiments, we also explored the impact of metadata features on the performance of dataset ranking. Our best performing submission achieved a score of 0.153, 0.161 and 0.174 in nDCG@10, nERR@10, and Q-measure, respectively. In all the metrics, this run was ranked 13th among 25 submitted runs.
Ghosh et al. (Tue,) studied this question.