"Similar query was answered earlier": processing of patient authored text for retrieving relevant contents from health discussion forum.

Health information retrieval Natural language processing Patient authored text Public health informatics Web forum analysis

Journal

Health information science and systems
ISSN: 2047-2501
Titre abrégé: Health Inf Sci Syst
Pays: England
ID NLM: 101638060

Informations de publication

Date de publication:
Dec 2019
Historique:
received: 30 06 2018
accepted: 01 02 2019
entrez: 14 3 2019
pubmed: 14 3 2019
medline: 14 3 2019
Statut: epublish

Résumé

Online remedy finders and health-related discussion forums have become increasingly popular in recent years. Common web users write their health problems there and request suggestion from experts or other users. As a result, these forums became a huge repository of information and discussions on various health issues. An intelligent information retrieval system can help to utilize this repository in various applications. In this paper, we propose a system for the automatic identification of existing similar forum posts given a new post. The system is based on computing similarity between two patient authored texts. For computing the similarity between the current post and existing posts, the system uses a hybrid strategy based on template information, topic modelling, and latent semantic indexing. The system is tested using a set of real questions collected from a homeopathy forum namely abchomeopathy.com. The relevance of the posts retrieved by the system is evaluated by human experts. The evaluation results demonstrate that the precision of the system is 88.87%.

Identifiants

pubmed: 30863540
doi: 10.1007/s13755-019-0067-3
pii: 67
pmc: PMC6384532
doi:

Types de publication

Journal Article

Langues

eng

Pagination

4

Déclaration de conflit d'intérêts

The authors declare that they have no conflict of interest.This article does not contain any studies with human participants or animals performed by any of the authors.Informed consent was obtained from all individual participants included in the study.

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Auteurs

Sujan Kumar Saha (SK)

1Department of Computer Science and Engineering, Birla Institute of Technology Mesra, Ranchi, 835215 India.

Amit Prakash (A)

1Department of Computer Science and Engineering, Birla Institute of Technology Mesra, Ranchi, 835215 India.

Mukta Majumder (M)

2Department of Computer Science and Application, University of North Bengal, West Bengal, India.

Classifications MeSH