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Supporting personalised content management in smart health information portals

De Silva, Daswin, Burstein, Frada and Fisher, Julie 2012, Supporting personalised content management in smart health information portals, in ACIS 2012 : Location, location, location : Proceedings of the 23rd Australasian Conference on Information Systems 2012, ACIS, [Geelong, Vic.], pp. 1-11.

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Title Supporting personalised content management in smart health information portals
Author(s) De Silva, Daswin
Burstein, Frada
Fisher, Julie
Conference name Australasian Conference on Information Systems (23rd : 2012 : Geelong, Victoria)
Conference location Geelong, Victoria
Conference dates 3-5 Dec. 2012
Title of proceedings ACIS 2012 : Location, location, location : Proceedings of the 23rd Australasian Conference on Information Systems 2012
Editor(s) Lamp, JohnORCID iD for Lamp, John orcid.org/0000-0003-1891-0400
Publication date 2012
Conference series Australasian Conference on Information Systems
Start page 1
End page 11
Total pages 11
Publisher ACIS
Place of publication [Geelong, Vic.]
Keyword(s) smart health information portal
personalised content management
automated content discovery
text mining
vector space model
query extraction
content discovery and ranking
Summary Information portals are seen as an appropriate platform for personalised healthcare and wellbeing information provision. Efficient content management is a core capability of a successful smart health information portal (SHIP) and domain expertise is a vital input to content management when it comes to matching user profiles with the appropriate resources. The rate of generation of new health-related content far exceeds the numbers that can be manually examined by domain experts for relevance to a specific topic and audience. In this paper we investigate automated content discovery as a plausible solution to this shortcoming that capitalises on the existing database of expert-endorsed content as an implicit store of knowledge to guide such a solution. We propose a novel content discovery technique based on a text analytics approach that utilises an existing content repository to acquire new and relevant content. We also highlight the contribution of this technique towards realisation of smart content management for SHIPs.
Notes Reproduced with the kind permission of the copyright owner.
Language eng
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
Related work DU:30049020
Copyright notice ©2012, The Authors/ACIS
Persistent URL http://hdl.handle.net/10536/DRO/DU:30049132

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Created: Fri, 26 Oct 2012, 11:30:14 EST

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