Learning to Rank for Consumer Health Search: A Semantic Approach

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, outperform...

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Bibliographic Details
Published inAdvances in Information Retrieval Vol. 10193; pp. 640 - 646
Main Authors Soldaini, Luca, Goharian, Nazli
Format Book Chapter
LanguageEnglish
Published Switzerland Springer International Publishing AG 2017
Springer International Publishing
SeriesLecture Notes in Computer Science
Subjects
Consumer health search
Learning to rank
Medical search
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Summary: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.
ISBN:3319566075
9783319566078
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-319-56608-5_60