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An intelligent content discovery technique for health portal content management

De Silva, Daswin and Burstein, Frada 2014, An intelligent content discovery technique for health portal content management, JMIR medical informatics, vol. 2, no. 1, pp. 1-7, doi: 10.2196/medinform.2671.

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Title An intelligent content discovery technique for health portal content management
Author(s) De Silva, Daswin
Burstein, Frada
Journal name JMIR medical informatics
Volume number 2
Issue number 1
Start page 1
End page 7
Total pages 7
Publisher JMIR Publications
Place of publication Toronto, Ont.
Publication date 2014
ISSN 2291-9694
Keyword(s) health information retrieval
personalised content management
health information portal
fuzzy multi-criteria ranking
automated content discovery
data analytics
text mining
Summary 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.
Language eng
DOI 10.2196/medinform.2671
Field of Research 159999 Commerce, Management, Tourism and Services not elsewhere classified
Socio Economic Objective 970115 Expanding Knowledge in Commerce, Management, Tourism and Services
HERDC Research category C1.1 Refereed article in a scholarly journal
Copyright notice ©2014, The Authors
Free to Read? Yes
Use Rights Creative Commons Attribution licence
Persistent URL http://hdl.handle.net/10536/DRO/DU:30063555

Document type: Journal Article
Collections: School of Information and Business Analytics
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Created: Fri, 23 May 2014, 09:42:24 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.