@InProceedings{jin-EtAl:2017:BioNLP17,
  author    = {Jin, Zan-Xia  and  Zhang, Bo-Wen  and  Fang, Fan  and  Zhang, Le-Le  and  Yin, Xu-Cheng},
  title     = {A Multi-strategy Query Processing Approach for Biomedical Question Answering: USTB\_PRIR at BioASQ 2017 Task 5B},
  booktitle = {BioNLP 2017},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada,},
  publisher = {Association for Computational Linguistics},
  pages     = {373--380},
  abstract  = {This paper describes the participation of USTB\_PRIR team in the 2017 BioASQ 5B
	on question answering, including document retrieval, snippet retrieval, and
	concept retrieval task. We introduce different multimodal query processing
	strategies to enrich query terms and assign different weights to them.
	Specifically, sequential dependence model (SDM), pseudo-relevance feedback
	(PRF), fielded sequential dependence model (FSDM) and Divergence from
	Randomness model (DFRM) are respectively performed on different fields of
	PubMed articles, sentences extracted from relevant articles, the five
	terminologies or ontologies (MeSH, GO, Jochem, Uniprot and DO) to achieve
	better search performances. Preliminary results show that our systems
	outperform others in the document and snippet retrieval task in the first two
	batches.},
  url       = {http://www.aclweb.org/anthology/W17-2348}
}