Supporting personalised content management in smart health information portals

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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, 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
Free to Read?	Yes
Persistent URL	http://hdl.handle.net/10536/DRO/DU:30049132

Document type:	Conference Paper
Collections:	ACIS : Proceedings of the 23rd Australasian Conference on Information Systems 2012 Open Access Collection


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