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An Intelligent Content Discovery Technique for Health Portal Content Management

BACKGROUND: Continuous content management of health information portals is a feature vital for its sustainability and widespread acceptance. Knowledge and experience of a domain expert is essential for content management in the health domain. The rate of generation of online health resources is expo...

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Detalles Bibliográficos
Autores principales: De Silva, Daswin, Burstein, Frada
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Gunther Eysenbach 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4288068/
https://www.ncbi.nlm.nih.gov/pubmed/25654440
http://dx.doi.org/10.2196/medinform.2671
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author De Silva, Daswin
Burstein, Frada
author_facet De Silva, Daswin
Burstein, Frada
author_sort De Silva, Daswin
collection PubMed
description BACKGROUND: Continuous content management of health information portals is a feature vital for its sustainability and widespread acceptance. Knowledge and experience of a domain expert is essential for content management in the health domain. The rate of generation of online health resources is exponential and thereby manual examination for relevance to a specific topic and audience is a formidable challenge for domain experts. Intelligent content discovery for effective content management is a less researched topic. An existing expert-endorsed content repository can provide the necessary leverage to automatically identify relevant resources and evaluate qualitative metrics. OBJECTIVE: This paper reports on the design research towards an intelligent technique for automated content discovery and ranking for health information portals. The proposed technique aims to improve efficiency of the current mostly manual process of portal content management by utilising an existing expert-endorsed content repository as a supporting base and a benchmark to evaluate the suitability of new content METHODS: A model for content management was established based on a field study of potential users. The proposed technique is integral to this content management model and executes in several phases (ie, query construction, content search, text analytics and fuzzy multi-criteria ranking). The construction of multi-dimensional search queries with input from Wordnet, the use of multi-word and single-word terms as representative semantics for text analytics and the use of fuzzy multi-criteria ranking for subjective evaluation of quality metrics are original contributions reported in this paper. RESULTS: The feasibility of the proposed technique was examined with experiments conducted on an actual health information portal, the BCKOnline portal. Both intermediary and final results generated by the technique are presented in the paper and these help to establish benefits of the technique and its contribution towards effective content management. CONCLUSIONS: The prevalence of large numbers of online health resources is a key obstacle for domain experts involved in content management of health information portals and websites. The proposed technique has proven successful at search and identification of resources and the measurement of their relevance. It can be used to support the domain expert in content management and thereby ensure the health portal is up-to-date and current.
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spelling pubmed-42880682015-01-15 An Intelligent Content Discovery Technique for Health Portal Content Management De Silva, Daswin Burstein, Frada JMIR Med Inform Original Paper BACKGROUND: Continuous content management of health information portals is a feature vital for its sustainability and widespread acceptance. Knowledge and experience of a domain expert is essential for content management in the health domain. The rate of generation of online health resources is exponential and thereby manual examination for relevance to a specific topic and audience is a formidable challenge for domain experts. Intelligent content discovery for effective content management is a less researched topic. An existing expert-endorsed content repository can provide the necessary leverage to automatically identify relevant resources and evaluate qualitative metrics. OBJECTIVE: This paper reports on the design research towards an intelligent technique for automated content discovery and ranking for health information portals. The proposed technique aims to improve efficiency of the current mostly manual process of portal content management by utilising an existing expert-endorsed content repository as a supporting base and a benchmark to evaluate the suitability of new content METHODS: A model for content management was established based on a field study of potential users. The proposed technique is integral to this content management model and executes in several phases (ie, query construction, content search, text analytics and fuzzy multi-criteria ranking). The construction of multi-dimensional search queries with input from Wordnet, the use of multi-word and single-word terms as representative semantics for text analytics and the use of fuzzy multi-criteria ranking for subjective evaluation of quality metrics are original contributions reported in this paper. RESULTS: The feasibility of the proposed technique was examined with experiments conducted on an actual health information portal, the BCKOnline portal. Both intermediary and final results generated by the technique are presented in the paper and these help to establish benefits of the technique and its contribution towards effective content management. CONCLUSIONS: The prevalence of large numbers of online health resources is a key obstacle for domain experts involved in content management of health information portals and websites. The proposed technique has proven successful at search and identification of resources and the measurement of their relevance. It can be used to support the domain expert in content management and thereby ensure the health portal is up-to-date and current. Gunther Eysenbach 2014-04-23 /pmc/articles/PMC4288068/ /pubmed/25654440 http://dx.doi.org/10.2196/medinform.2671 Text en ©Daswin De Silva, Frada Burstein. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 23.04.2014. http://creativecommons.org/licenses/by/2.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on http://medinform.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
De Silva, Daswin
Burstein, Frada
An Intelligent Content Discovery Technique for Health Portal Content Management
title An Intelligent Content Discovery Technique for Health Portal Content Management
title_full An Intelligent Content Discovery Technique for Health Portal Content Management
title_fullStr An Intelligent Content Discovery Technique for Health Portal Content Management
title_full_unstemmed An Intelligent Content Discovery Technique for Health Portal Content Management
title_short An Intelligent Content Discovery Technique for Health Portal Content Management
title_sort intelligent content discovery technique for health portal content management
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4288068/
https://www.ncbi.nlm.nih.gov/pubmed/25654440
http://dx.doi.org/10.2196/medinform.2671
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