216 research outputs found
Customization of Web applications through an intelligent environment exploiting logical interface descriptions
This is the author’s version of a work that was accepted for publication in Interacting with Computers. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Interacting with Computers, 20, 1 (2008) DOI:10.1016/j.intcom.2007.07.007Customization of Web-based applications is often considered a designer skill rather than an end-user need. However, there is an ongoing shift to end-user-centred technology, and even users with poor or no skill in Web-based languages may feel the need to customize Web applications according to their preferences. Although Web authoring environments have an increasing number of features, the challenge of providing end-users with the ability to easily customize entire Web applications still remains unsolved. In this paper, we propose an intelligent approach to customizing Web-based applications. Customizations rules are automatically inferred by the system from changes that users supply as examples. They remain as long-term knowledge that can be applied to support future interactions, thus minimizing the amount of authoring that end-users need to do for this purpose. In order to better understand the implications of the user's modifications, they are analysed using the logical descriptions of the corresponding Web pages.The work reported in this paper is supported by the European Training Network ADVISES (Analysis Design and Validation of Interactive Safety-critical and Error-tolerant Systems), funded through the European Commission. Project number EU HPRN-CT-2002-00288
Intelligent support for end-user web interface customization
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-540-92698-6_19Proceedings of Selected Papers EIS 2007 Joint Working Conferences, EHCI 2007, DSV-IS 2007, HCSE 2007, Salamanca, Spain.Nowadays, while the number of users of interactive software steadily increase, new applications and systems appear and provide further complexity. An example of such systems is represented by multi-device applications, where the user can interact with the system through different platforms. However, providing end-users with real capabilities to author user interfaces is still a problematic issue, which is beyond the ability of most end-users today. In this paper, we present an approach intended to enable users to modify Web
interfaces easily, considering implicit user intents inferred from example interface modifications carried out by the user. We discuss the design issues involved in the implementation of such an intelligent approach, also reporting on some experimental results obtained from a user test.The work reported in this paper ha been supported by the European Training Network ADVISES, project EU HPRN-CT-2002-00288, and by the Spanish Ministry of Science and Technology (MCyT), projects TIN2005-06885 and TSI2005-08225-C07-0
Public policies and multilingualism in HCI
International audiencePublic policy plays an influential role in the work we do as HCI researchers, interaction designers, and practitioners. "Public policy," a broad term, includes both government policy and policy within non-governmental organizations. This forum focuses on topics at the intersection of human-computer interaction and public policy
How to exploit abstract user interfaces in MARIA
In model-based approaches, Abstract User Interfaces enable the specification of interactive applications in a modality-independent manner, which is then often used for authoring multi-device interactive applications. In this paper we discuss two solutions for exploiting abstract UIs. We consider the MARIA language for such comparison. The overall aim is to improve the efficiency of the model-based process, thus making it easier to adopt and apply
How to exploit abstract user interfaces in MARIA
In model-based approaches, Abstract User Interfaces enable the specification of interactive applications in a modality-independent manner, which is then often used for authoring multi-device interactive applications. In this paper we discuss two solutions for exploiting abstract UIs. We consider the MARIA language for such comparison. The overall aim is to improve the efficiency of the model-based process, thus making it easier to adopt and apply
A set of languages for context-aware adaptation
The creation of service front ends able to adapt to the context of use involves a wide spectrum of aspects to be considered by developers and designers. A context-aware adaptation enabled application needs a simultaneous management of very different application functionalities, such as the context sensing, identifying different given situations, determining the appropriate reactions and the execution of the adaptation effects. In this paper we describe an adaptation architecture for tackling this complexity and we present a set of languages that address the definition of the various aspects of an adaptive application
Model-based customizable adaptation of web applications for vocal browsing
In this paper we describe a solution to make Web pages more suitable for vocal browsing by analyzing and modifying their logical structure. The solution exploits intermediate logical descriptions that are automatically created by reverse engineering techniques. The adaptation engine aims to identify the main logical structure of the Web page components and remove the aspects specific to the graphical modality. Then, a vocal implementation is generated to support browsing, which begins by the user’s selecting from the main components. It is possible to customize some parameters of the adaptation transformation in order to better control its results
USING STUDENT MENTAL STATE AND LEARNING SENSORY MODALITIES TO IMPROVE ADAPTIVITY IN E-LEARNING
  In this paper, we present an innovative solution to improve adaptivity in an e-learning system using Brain Computer Interface (BCI) measures (Attention/Meditation) in order to detect changes in students’ preferred perceptual modes for learning information (VARK model). Our solution is also able to report course units and learning resources that could be difficult for the students
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