Consumer Health Question Answering Using Off-the-Shelf Components

Pugachev, Alexander; Artemova, Ekaterina; Bondarenko, Alexander und Braslavski, Pavel (2023): Consumer Health Question Answering Using Off-the-Shelf Components. 45th European Conference on Information Retrieval (ECIR), Dublin, Ireland, 02. - 06. April 2023. Kamps, Jaap; Goeuriot, Lorraine; Crestani, Fabio; Maistro, Maria; Joho, Hideo; Davis, Brian; Gurrin, Cathal; Kruschwitz, Udo und Caputo, Annalina (Hrsg.): In: Advances in Information Retrieval : 45th European Conference on Information Retrieval, ECIR 2023, Dublin, Ireland, April 2–6, 2023, proceedings, part II, Lecture Notes in Computer Science Bd. 13981 Cham: Springer. S. 571-579

Abstract

In this paper, we address the task of open-domain health question answering (QA). The quality of existing QA systems heavily depends on the annotated data that is often difficult to obtain, especially in the medical domain. To tackle this issue, we opt for PubMed and Wikipedia as trustworthy document collections to retrieve evidence. The questions and retrieved passages are passed to off-the-shelf question answering models, whose predictions are then aggregated into a final score. Thus, our proposed approach is highly data-efficient. Evaluation on 113 health-related yes/no question and answer pairs demonstrates good performance achieving AUC of 0.82.

• Dokumententyp: Konferenzbeitrag (Paper)
• Fakultätsübergreifende Einrichtungen: Centrum für Informations- und Sprachverarbeitung (CIS)
• Themengebiete: 000 Informatik, Informationswissenschaft, allgemeine Werke > 004 Informatik ; 400 Sprache > 410 Linguistik ; 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit
• ISBN: 978-3-031-28237-9 ; 978-3-031-28238-6 ; 978-3-031-28239-3
• ISSN: 0302-9743
• Ort: Cham
• Sprache: Englisch