Author(s):  
HILARY J. HOLZ ◽  
KATJA HOFMANN ◽  
CATHERINE REED

We propose a technique for user modeling in Adaptive Hypermedia (AH) that is unobtrusive at both the level of observable behavior and that of cognition. Unobtrusive user modeling is complementary to transparent user modeling. Unobtrusive user modeling induces user models appropriate for Educational AH (EAH) based on metaphors characterized by a shared locus of control over learning, such as small group learning. Transparent user modeling, on the other hand, induces user models appropriate for EAH based on metaphors characterized by an independent locus of control, such as social navigation. We extend an existing decomposition model of adaptation in AH to incorporate summative evaluation of unobtrusive user modeling. Summative evaluation examines the effects or outcomes of a system, while formative evaluation is used to improve a system under development. We also introduce a separate, two-stage model for formative evaluation of unobtrusive user modeling. We then present results from a field study for the first of the two developmental stages and describe the current field study of the second developmental stage. Finally, we compare unobtrusive and transparent user modeling, and explain the role of each.


Author(s):  
Miguel-Ángel Sicila ◽  
Elena García Barriocanal

daptive hypermedia applications are aimed at tailoring hypermedia structures according to some form of user model, in an attempt to increase the usability and utility of the application for each individual or group. Existing research in the field has resulted in many systems, techniques, and paradigms, both for modelling user data and for the subsequent exploitation of such model for the sake of personalisation. As a matter of fact, the majority of adaptive hypermedia systems work with user models that are imperfect in some way, and the theories or hypotheses that guide adaptation are also often of a heuristic or approximate nature. Although some existing systems provide explicit means for dealing with imperfection in one or several of its multiple facets, there exists a lack of support for information imperfection in adaptive hypermedia models and architectures. In an attempt to provide such conceptual support, the MAZE model was proposed as a generalisation of an existing abstract hypermedia model, providing built-in support for fuzzy set-theoretic notions. This chapter provides an overall account of the MAZE model, along with its rationale, and an overview of a possible instance of a MAZE-based architecture. In addition, the use of MAZE to model common adaptive hypermedia technologies is illustrated through a concrete case study.


Author(s):  
Ana Carolina Tomé Klock ◽  
Isabela Gasparini ◽  
Marcelo Soares Pimenta ◽  
José Palazzo M. de Oliveira

Adaptive hypermedia systems are systems that modify the different visible aspects based on the user profile. To provide this adaptation, the system is modeled according to a user model, which stores the information about each user. This information can include knowledge, interests, goals and tasks, background and skills, behavior, interaction preferences, individual traits, and context of the user. This chapter's goal is to introduce adaptive hypermedia systems fundamentals and trends. In this context, this chapter identifies some methods and techniques used to adapt the content, the presentation, and the navigation of the system. In the end, some applications (ELM-ART, Interbook, AHA!, AdaptWeb®) and trends (standardization, data mining, social web, device adaptation, and gamification) are exposed. As a result, this chapter highlights the importance of the improvement and the use of adaptive systems.


Author(s):  
Sandro José Rigo

Adaptive Hypermedia is an effective approach to automatic personalization that overcomes the difficulties and deficiencies of traditional Web systems in delivering the appropriate content to users. One important issue regarding Adaptive Hypermedia systems is the construction and maintenance of the user profile. Another important concern is the use of Semantic Web resources to describe Web applications and to implement adaptation mechanisms. Web Usage Mining, in this context, allows the generation of Websites access patterns. This chapter describes the possibilities of integration of these usage patterns with semantic knowledge obtained from domain ontologies. Thus, it is possible to identify users’ stereotypes for dynamic Web pages customization. This integration of semantic knowledge can provide personalization systems with better adaptation strategies.


2008 ◽  
pp. 148-167
Author(s):  
Alexandros Paramythis ◽  
Constantine Stephanidis

This chapter introduces a framework intended for facilitating the implementation of Web-based adaptive hypermedia systems. The framework is orthogonal to Web “serving” approaches, and poses only minimal requirements in that direction. As such, it can be easily integrated into existing, non-adaptive Web-publishing solutions. This chapter presents in detail several aspects of the framework, and provides an overview of its application in the European Commission-funded IST-1999-20656 PALIO project (“Personalised Access to Local Information and Services for Tourists”). Furthermore, it discusses some of the lessons learned from our work on the framework thus far, as well as what we consider the most likely directions of future work in the area.


2011 ◽  
pp. 1388-1410
Author(s):  
Sandro José Rigo ◽  
José M. Palazzo de Oliveira ◽  
Leandro Krug Wives

Adaptive Hypermedia is an effective approach to automatic personalization that overcomes the difficulties and deficiencies of traditional Web systems in delivering the appropriate content to users. One important issue regarding Adaptive Hypermedia systems is the construction and maintenance of the user profile. Another important concern is the use of Semantic Web resources to describe Web applications and to implement adaptation mechanisms. Web Usage Mining, in this context, allows the generation of Websites access patterns. This chapter describes the possibilities of integration of these usage patterns with semantic knowledge obtained from domain ontologies. Thus, it is possible to identify users’ stereotypes for dynamic Web pages customization. This integration of semantic knowledge can provide personalization systems with better adaptation strategies.


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