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Scientific Information Research

Keywords

online health community; expert finding; knowledge graph; entity relation joint extraction; reliability

Abstract

[Purpose/ significance] This study aims to identify the expertise domains of medical experts, and evaluates their domain levels to provide a basis for community expert recommendation.

[Method/process] This study utilized the improved OneRel model to structure community historical Q&A into entity relation triples. Then used the knowledge graph triples to test the consistency between the medical knowledge in the community Q&A and the domain knowledge, and finally obtained the doctor's domain levels by aggregating in each expertise domain.

[Result/conclusion] Using the data example from xywy.com website, 214 doctors in the community were ranked in terms of their average level of expertise domains and their respective reliable domains levels were identified. The study verified that the basic information self-reported by doctors in online health communities, such as their expertise and personal profiles, did not fully correspond to their real competence characteristics. Compared with other medical expert discovery methods, this method can intelligently identify and evaluate doctors' expertise domains, demonstrating objectivity, accuracy, and strong interpretability.

First Page

24

Last Page

34

Digital Object Identifier (DOI)

ꎺ 10.19809/j.cnki.kjqbyj.2025.04.003

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