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Links Personalisation with Multi-Dimensional Linkbases

Links Personalisation with Multi-Dimensional Linkbases
Links Personalisation with Multi-Dimensional Linkbases
Adaptive hypermedia has provided a way information can be presented online. Based on adaptive presentation and adaptive navigational support, a static page can now be dynamically personalised for an individual user. Users who possess different needs, interests and background knowledge can now be provided with a different presentation of the same information. Many frameworks for adaptive hypermedia systems and applications have been proposed that use different strategies. This thesis proposes a new approach for the presentation and personalisation of links based on the idea of a multi-dimensional linkbase. It is the notion that describes a single linkbase that contains links annotated with metadata that place the links in several different contextual dimensions at once. These sets of links signify different dimensions of expertise of the user and are encoded to condition the visibility of links. This work builds upon the implementation of FOHM and Auld Linky at Southampton University. To provide users with control over the personalisation of their links, the users are provided with navigational tools for the presentation of these links. The presentation of the links depends on the preferences of the users and the linkbases they have enabled and disabled. This facilitates flexibility and reduces the user syndrome of ‘too many-irrelevant-additional links’. Four straightforward adaptive systems have been developed to demonstrate the diversity of the link service approach, and in particular the concept of a multi-dimensional linkbase, which has been applied into a Web-based prototype, an inquiry-led personalised navigation system. This thesis also documents the formal evaluation studies undertaken, which demonstrates that such a proposal is practicable and meaningful to a user.
Longpradit, Panchit
651e024a-3cfc-4d2e-b73e-dce93202f2f5
Longpradit, Panchit
651e024a-3cfc-4d2e-b73e-dce93202f2f5

(2007) Links Personalisation with Multi-Dimensional Linkbases. University of Southampton, School of Electronics and Computer Science, Doctoral Thesis.

Record type: Thesis (Doctoral)

Abstract

Adaptive hypermedia has provided a way information can be presented online. Based on adaptive presentation and adaptive navigational support, a static page can now be dynamically personalised for an individual user. Users who possess different needs, interests and background knowledge can now be provided with a different presentation of the same information. Many frameworks for adaptive hypermedia systems and applications have been proposed that use different strategies. This thesis proposes a new approach for the presentation and personalisation of links based on the idea of a multi-dimensional linkbase. It is the notion that describes a single linkbase that contains links annotated with metadata that place the links in several different contextual dimensions at once. These sets of links signify different dimensions of expertise of the user and are encoded to condition the visibility of links. This work builds upon the implementation of FOHM and Auld Linky at Southampton University. To provide users with control over the personalisation of their links, the users are provided with navigational tools for the presentation of these links. The presentation of the links depends on the preferences of the users and the linkbases they have enabled and disabled. This facilitates flexibility and reduces the user syndrome of ‘too many-irrelevant-additional links’. Four straightforward adaptive systems have been developed to demonstrate the diversity of the link service approach, and in particular the concept of a multi-dimensional linkbase, which has been applied into a Web-based prototype, an inquiry-led personalised navigation system. This thesis also documents the formal evaluation studies undertaken, which demonstrates that such a proposal is practicable and meaningful to a user.

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More information

Published date: June 2007
Organisations: University of Southampton, Electronics & Computer Science

Identifiers

Local EPrints ID: 266375
URI: http://eprints.soton.ac.uk/id/eprint/266375
PURE UUID: 9ac8c658-6bd7-4557-b220-4b115a282fa8

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Date deposited: 28 Jul 2008 07:14
Last modified: 26 Jun 2018 16:31

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Contributors

Author: Panchit Longpradit

University divisions

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