%0 Conference Proceedings %T Query selection methods for automated corpora construction with a use case in food-drug interactions %A Bordea, Georgeta %A Randriatsitohaina, Tsanta %A Mougin, Fleur %A Grabar, Natalia %A Hamon, Thierry %Y Demner-Fushman, Dina %Y Cohen, Kevin Bretonnel %Y Ananiadou, Sophia %Y Tsujii, Junichi %S Proceedings of the 18th BioNLP Workshop and Shared Task %D 2019 %8 August %I Association for Computational Linguistics %C Florence, Italy %F bordea-etal-2019-query %X In this paper, we address the problem of automatically constructing a relevant corpus of scientific articles about food-drug interactions. There is a growing number of scientific publications that describe food-drug interactions but currently building a high-coverage corpus that can be used for information extraction purposes is not trivial. We investigate several methods for automating the query selection process using an expert-curated corpus of food-drug interactions. Our experiments show that index term features along with a decision tree classifier are the best approach for this task and that feature selection approaches and in particular gain ratio outperform frequency-based methods for query selection. %R 10.18653/v1/W19-5013 %U https://aclanthology.org/W19-5013 %U https://doi.org/10.18653/v1/W19-5013 %P 115-124