Assessment of Human Factors in Adaptive Hypermedia Environments

Assessment of Human Factors in Adaptive Hypermedia Environments

Nikos Tsianos (National & Kapodistrian University of Athens, Greece), Panagiotis Germanakos (National & Kapodistrian University of Athens, Greece), Zacharias Lekkas (National & Kapodistrian University of Athens, Greece) and Constantinos Mourlas (National & Kapodistrian UniversityNational & Kapodistrian University of Athens, Greece)
DOI: 10.4018/978-1-60566-032-5.ch001
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The plethora of information and services as well as the complicated nature of most Web structures intensify the navigational difficulties that arise when users navigate their way through this large information space. Personalized services that are highly sensitive to the immediate environment and the goals of the user can alleviate the orientation and presentation difficulties experienced by the relatively diverse user population. User profiles serves as the main component of most Web personalization systems. Main scope of this chapter is to present the various techniques employed by such systems with regards to user profiles extraction and introduce a comprehensive user profile, which includes User Perceptual Preference Characteristics. It further analyzes the main intrinsic users’ characteristics like visual, cognitive, and emotional processing parameters incorporated as well as the “traditional” user profile characteristics that together tend to give the most optimized personalization outcome. It finally overviews a Web adaptation and personalization system and presents evaluation results that further support the importance of human factors in the information space.
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The unprecedented and constant expansion of the World Wide Web coupled with the obscure and multi-component nature of its structure, result in orientation difficulties, as users often lose sight of the goal of their inquiry, look for stimulating rather than informative material, or even use the navigational features unwisely. As the e-Services sector is rapidly evolving, the need for such Web structures that satisfy the heterogeneous needs of its users is becoming more and more evident.

To alleviate such navigational and presentation difficulties, researchers have put huge amounts of effort to identify the peculiarities of each user group and analyze and design methodologies and systems that could deliver up-to-date adaptive and personalized information, with regards to products or services. Since to date, there has not been a concrete definition of personalization. The many adaptive hypermedia and Web personalization solutions offering personalization features meet an abstract common goal: to provide users with what they want or need without expecting them to ask for it explicitly (Mulvenna et al., 2000). Further consideration and analysis of parameters and contexts such as users intellectuality, mental capabilities, socio-psychological factors, emotional states and attention grabbing strategies, that could affect the apt collection of users’ customization requirements offering in return the best adaptive environments to their preferences and demands should be extensively investigated. All these characteristics, along with the “traditional” user characteristics that is, name, age, education, experience, etc., constitute a comprehensive user profile that serves as the ground element of most of these systems.

Some noteworthy, mostly commercial, applications in the area of Web personalization that collects information with various techniques from the users based on which they construct their user profile and further adapt the services content provided, are amongst others the Broadvision’s One-To-One, a commercial tool for identification of on-line users; Microsoft’s Firefly Passport (developed by the MIT Media Lab); the Macromedia’s LikeMinds Preference Server, which identifies behaviours of on-line customers and it further predicts new purchases of a user; Apple’s WebObjects, which adapts the content to user preferences, etc. Other, more research oriented systems, include ARCHIMIDES (Bogonicolos et al., 1999), which adapts the raw content based on the structure reorganization of a Web server. The structure is depicted as a semantic tree through of which there is a dynamic selection of the content nodes according to the users’ preferences; Proteus (Anderson, 2001), is a system that construct user models using artificial intelligence techniques and adapts the content of a Web site taking into consideration also wireless connections; WBI (Maglio & Barret, 2000; Barret et. al, 1997) and BASAR (Thomas & Fischer, 1997), use static agents for the personalization of the content while other systems employ mobile agents over mobile networks for this purpose, like mPERSONA (Panayiotou & Samaras, 2003). Significant implementations have also been developed in the area of adaptive hypermedia, with regards to the provision of adapted educational content to students using various adaptive hypermedia techniques. Such systems are amongst others, INSPIRE (Papanikolaou et al., 2003), ELM-ART (Weber & Specht, 1997), AHA! (De Bra & Calvi, 1998), Interbook (Brusilovsky et. al., 1998), and so on.

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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