A Semantically Adaptive Interface for Measuring Portal Quality in E-Government

A Semantically Adaptive Interface for Measuring Portal Quality in E-Government

Babis Magoutas (National Technical University of Athens, Greece.)
DOI: 10.4018/978-1-60566-032-5.ch007
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This chapter introduces a semantically adaptive interface as a means of measuring the quality of egovernment portals, based on user feedback. The interface is semantic as it uses ontologies in order to formalize well defined semantics about the adaptation criteria used. Furthermore it is adaptive as three axes of adaptation are applied: based on real-time feedback from users, based on problems encountered by the user and based on metadata of the pages visited by the user. The authors hope that applying the proposed adaptive interface as a means of measuring e-government portals’ quality, will not only allow more focused and targeted assessment of quality, but will also increase users’ response rates.
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A research area which is very close to our work refers to adaptive hypermedia. An Adaptive Hypermedia System (AHS) tries to adapt information for a user based on a model of that particular user. Examples of adaptive hypermedia systems include AHA! (Bra et. al., 2003), ELM-ART (Brusilovsky et. al., 1996), and Adaptive Engine 3 - AE3 (Keeffe et. al., 2005). These systems use adaptive techniques in order to provide the adapted hypermedia for a user. There are four such techniques, which are adaptive navigation, adaptive presentation, structural adaptation, and historical adaptation (Tallon, 2005). Our approach uses the idea of adaptive presentation for quality measuring of e-government portals and services. Adaptive presentation is intuitively related to how the hypermedia is presented to the user. The hypermedia or content is adapted towards the user model provided. In our approach the adaptation is based on a user model that is constructed during runtime, using data mining on web server log and is modelled using semantic technologies (Apostolou et. al., 2006).

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Editorial Advisory Board
Table of Contents
Barry Smyth
Constantinos Mourlas, Panagiotis Germanakos
Constantinos Mourlas, Panagiotis Germanakos
Chapter 1
Nikos Tsianos, Panagiotis Germanakos, Zacharias Lekkas, Constantinos Mourlas
The plethora of information and services as well as the complicated nature of most Web structures intensify the navigational difficulties that arise... Sample PDF
Assessment of Human Factors in Adaptive Hypermedia Environments
Chapter 2
Barry Smyth
Everyday hundreds of millions of users turn to the World-Wide Web as their primary source of information during their educational, business and... Sample PDF
Case Studies in Adaptive Information Access: Navigation, Search, and Recommendation
Chapter 3
Sherry Y. Chen
Web-based instruction is prevalent in educational settings. However, many issues still remain to be investigated. In particular, it is still open... Sample PDF
The Effects of Human Factors on the Use of Web-Based Instruction
Chapter 4
Gulden Uchyigit
Coping with today’s unprecedented information overload problem necessitates the deployment of personalization services. Typical personalization... Sample PDF
The Next Generation of Personalization Techniques
Chapter 5
Nancy Alonistioti
This chapter introduces context-driven personalisation of service provision based on a middleware architectural approach. It describes the emerging... Sample PDF
Advanced Middleware Architectural Aspects for Personalised Leading-Edge Services
Chapter 6
Syed Sibte Raza Abidi
This chapter introduces intelligent information personalization as an approach to personalize the webbased information retrieval experiences based... Sample PDF
Intelligent Information Personalization: From Issues to Strategies
Chapter 7
Babis Magoutas
This chapter introduces a semantically adaptive interface as a means of measuring the quality of egovernment portals, based on user feedback. The... Sample PDF
A Semantically Adaptive Interface for Measuring Portal Quality in E-Government
Chapter 8
Fabio Grandi, Federica Mandreoli, Riccardo Martoglia, Enrico Ronchetti, Maria Rita Scalas
While the World Wide Web user is suffering form the disease caused by information overload, for which personalization is one of the treatments which... Sample PDF
Ontology-Based Personalization of E-Government Services
Chapter 9
Maria Golemati, Costas Vassilakis, Akrivi Katifori, George Lepouras, Constantin Halatsis
Novel and intelligent visualization methods are being developed in order to accommodate user searching and browsing tasks, including new and... Sample PDF
Context and Adaptivity-Driven Visualization Method Selection
Chapter 10
Honghua Dai
Web usage mining has been used effectively as an approach to automatic personalization and as a way to overcome deficiencies of traditional... Sample PDF
Integrating Semantic Knowledge with Web Usage Mining for Personalization
Chapter 11
Constantinos Mourlas
One way to implement adaptive software is to allocate resources dynamically during run-time rather than statically at design time. Design of... Sample PDF
Adaptive Presentation and Scheduling of Media Streams on Parallel Storage Servers
Chapter 12
Gheorghita Ghinea
This study investigated two dimensions of cognitive style, including Verbalizer/Imager and Field Dependent/ Field Independent and their influence on... Sample PDF
Impact of Cognitive Style on User Perception of Dynamic Video Content
Chapter 13
Mathias Bauer, Alexander Kröner, Michael Schneider, Nathalie Basselin
Limitation of the human memory is a well-known issue that anybody has experienced. This chapter discusses typical components and processes involved... Sample PDF
Building Digital Memories for Augmented Cognition and Situated Support
Chapter 14
Rafael Morales, Nicolas Van Labeke, Paul Brna, María Elena Chan
It is believed that, with the help of suitable technology, learners and systems can cooperate in building a sufficiently accurate learner model they... Sample PDF
Open Learner Modelling as the Keystone of the Next Generation of Adaptive Learning Environments
Chapter 15
Klaus Jantke, Christoph Igel, Roberta Sturm
Humans need assistance in learning. This is particularly true when learning is supported by modern information and communication technologies. Most... Sample PDF
From E-Learning Tools to Assistants by Learner Modelling and Adaptive Behavior
Chapter 16
Violeta Damjanovic, Milos Kravcik
The process of training and learning in Web-based and ubiquitous environments brings a new sense of adaptation. With the development of more... Sample PDF
Using Emotional Intelligence in Personalized Adaptation
Chapter 17
Yang Wang
This chapter presents a first-of-its-kind survey that systematically analyzes existing privacy-enhanced personalization (PEP) solutions and their... Sample PDF
Technical Solutions for Privacy- Enhanced Personalization
About the Contributors