Semantic linking and personalization in context
Semantic linking and personalization in context
The World Wide Web (WWW) is intended for humans to create and share documents. However, it does not support machine-processable data and automated processing. The Semantic Web is an extension to the WWW and can overcome its shortcomings. The Semantic Web provides the technology for creating and sharing data in machineprocessable semantics. As a result, the data can be used and shared in effective ways between cross applications.
In this thesis, we investigate the Semantic Web technologies for context-based hyperlink creation and personalization. Two different contributions are presented using Semantic Web technologies. First, we introduce and implement a novel personalized Semantic Web-enabled portal (known as a semantic portal), which is called SEMPort with the aim of improving information discovery and information sharing using the Semantic Web technologies. We also provide different Adaptive Hypermedia (AH) methods using ontology-based user models. In our second contribution, we introduce and implement a novel personalized Semantic Web browser, called SemWeB which is a browser that augments Web documents with metadata. It creates and personalizes context-based hyperlinks and data using ontologies. We have also developed a new behaviour-based user model for Web-based personalization which supports different AH methods. In addition, a novel semantic relatedness measure is proposed.
The evaluations showed that our contributions to the development of hypertext systems using Semantic Web technologies are successfully applied for context-based link
creation and personalization.
semantic web, adaptive hypermedia, user modelling, semantic annotation, dynamic linking, linked data
Şah, Melike
ea70cff7-5ecd-4dbc-a579-0c128a71072f
June 2009
Şah, Melike
ea70cff7-5ecd-4dbc-a579-0c128a71072f
Hall, Wendy
11f7f8db-854c-4481-b1ae-721a51d8790c
De Roure, David
02879140-3508-4db9-a7f4-d114421375da
Şah, Melike
(2009)
Semantic linking and personalization in context.
University of Southampton, School of Electronics and Computer Science, Doctoral Thesis, 305pp.
Record type:
Thesis
(Doctoral)
Abstract
The World Wide Web (WWW) is intended for humans to create and share documents. However, it does not support machine-processable data and automated processing. The Semantic Web is an extension to the WWW and can overcome its shortcomings. The Semantic Web provides the technology for creating and sharing data in machineprocessable semantics. As a result, the data can be used and shared in effective ways between cross applications.
In this thesis, we investigate the Semantic Web technologies for context-based hyperlink creation and personalization. Two different contributions are presented using Semantic Web technologies. First, we introduce and implement a novel personalized Semantic Web-enabled portal (known as a semantic portal), which is called SEMPort with the aim of improving information discovery and information sharing using the Semantic Web technologies. We also provide different Adaptive Hypermedia (AH) methods using ontology-based user models. In our second contribution, we introduce and implement a novel personalized Semantic Web browser, called SemWeB which is a browser that augments Web documents with metadata. It creates and personalizes context-based hyperlinks and data using ontologies. We have also developed a new behaviour-based user model for Web-based personalization which supports different AH methods. In addition, a novel semantic relatedness measure is proposed.
The evaluations showed that our contributions to the development of hypertext systems using Semantic Web technologies are successfully applied for context-based link
creation and personalization.
Text
PhD_Thesis_Melike_Sah.pdf
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More information
Published date: June 2009
Keywords:
semantic web, adaptive hypermedia, user modelling, semantic annotation, dynamic linking, linked data
Organisations:
University of Southampton
Identifiers
Local EPrints ID: 66605
URI: http://eprints.soton.ac.uk/id/eprint/66605
PURE UUID: f705a1e2-3e0d-44aa-8a40-af3ee871a5fe
Catalogue record
Date deposited: 01 Jul 2009
Last modified: 14 Mar 2024 02:32
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Contributors
Author:
Melike Şah
Thesis advisor:
David De Roure
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