Abstract
For many internet users, searching for health advice online is the first step in seeking treatment. We present a Learning to Rank system that uses a novel set of syntactic and semantic features to improve consumer health search. Our approach was evaluated on the 2016 CLEF eHealth dataset, outperforming the best method by 26.6% in NDCG@10.
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CITATION STYLE
APA
Soldaini, L., & Goharian, N. (2017). Learning to rank for consumer health search: A semantic approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10193 LNCS, pp. 640–646). Springer Verlag. https://doi.org/10.1007/978-3-319-56608-5_60
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