They are consistent individual differences in preferred ways of organizing and processing information and experience
Published in Chapter:
The Role of Human Factors in Web Personalization Environments
Panagiotis Germanakos (National & Kapodistrian University of Athens, Greece), Nikos Tsianos (National & Kapodistrian University of Athens, Greece), Zacharias Lekkas (National & Kapodistrian University of Athens, Greece), and Constantinos Mourlas (National & Kapodistrian University ofNational & Kapodistrian University of Athens, Greece)
Copyright: © 2009
|Pages: 7
DOI: 10.4018/978-1-60566-026-4.ch530
Abstract
The explosive growth in the size and use of the World Wide Web as a communication medium as well as the new developments in ICT allowed service providers to meet these challenges, developing new ways of interactions through a variety of channels enabling users to become accustomed to new means of service consumption in an “anytime, anywhere and anyhow” manner. However, the nature of most information structures is static and complicated, and users often lose sight of the goal of their inquiry, look for stimulating rather than informative material, or even use the navigational features unwisely. Hence, researchers and practitioners studied adaptivity and personalization to address the comprehension and orientation difficulties presented in such systems, to alleviate such navigational difficulties and satisfy the heterogeneous needs of the users, allowing at the same time Web applications of this nature to survive. There are many approaches to address these issues of personalization but usually, each one is focused upon a specific area, that is, whether this is profile creation, machine learning and pattern matching, data and Web mining or personalized navigation. Some noteworthy, mostly commercial, applications in the area of Web personalization that collect information with various techniques and further adapts the services provided, are among others the Broadvision’s One-To-One, Microsoft’s Firefly Passport, the Macromedia’s LikeMinds Preference Server, the Apple’s WebObjects, and so forth. Other, more research-oriented systems, include ARCHIMIDES (Bogonikolos et al., 1999), Proteus (Anderson et al., 2001), WBI (Magglio & Barret, 2001), BASAR (Thomas & Fischer, 1997), and mPERSONA (Panayiotou & Samaras, 2004). 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, among others, INSPIRE (Papanikolaou, Grigoriadou, Kornilakis, & Magoulas, 2003), ELM-ART (Weber & Specht, 1997), AHA! (De Bra & Calvi, 1998), Interbook (Brusilovsky, Eklund, & Schwartz, 1998), and so forth.