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A survey of consumer health question answering systems.

Authors :
Welivita, Anuradha
Pu, Pearl
Source :
AI Magazine; Dec2023, Vol. 44 Issue 4, p482-507, 26p
Publication Year :
2023

Abstract

Consumers are increasingly using the web to find answers to their health‐related queries. Unfortunately, they often struggle with formulating the questions, further compounded by the burden of having to traverse long documents returned by the search engine to look for reliable answers. To ease these burdens for users, automated consumer health question answering systems try to simulate a human professional by refining the queries and giving the most pertinent answers. This article surveys state‐of‐the‐art approaches, resources, and evaluation methods used for automatic consumer health question answering. We summarize the main achievements in the research community and industry, discuss their strengths and limitations, and finally come up with recommendations to further improve these systems in terms of quality, engagement, and human‐likeness. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
07384602
Volume :
44
Issue :
4
Database :
Complementary Index
Journal :
AI Magazine
Publication Type :
Academic Journal
Accession number :
174107431
Full Text :
https://doi.org/10.1002/aaai.12140