A study of similar question retrieval method in online health communities

Bufei Xing, Haonan Yin, Zhijun Yan*, Jiachen Wang

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    3 Citations (Scopus)

    Abstract

    Purpose: The purpose of this paper is to propose a new approach to retrieve similar questions in online health communities to improve the efficiency of health information retrieval and sharing. Design/methodology/approach: This paper proposes a hybrid approach to combining domain knowledge similarity and topic similarity to retrieve similar questions in online health communities. The domain knowledge similarity can evaluate the domain distance between different questions. And the topic similarity measures questions’ relationship base on the extracted latent topics. Findings: The experiment results show that the proposed method outperforms the baseline methods. Originality/value: This method conquers the problem of word mismatch and considers the named entities included in questions, which most of existing studies did not.

    Original languageEnglish
    Pages (from-to)154-165
    Number of pages12
    JournalInternational Journal of Crowd Science
    Volume5
    Issue number2
    DOIs
    Publication statusPublished - 3 Aug 2021

    Keywords

    • Named entity extraction
    • Online health communities
    • Question retrieval
    • Topic model

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