Multichannel Adaptive Web Information Systems (WISs) are emerging as a new class of information systems, characterized by their powerful use of mobility and context-awareness. Different methodologies have been proposed so far for the analysis and design of Multichannel Adaptive WISs, specifically focused on the front-end layer or the back-end layer, but no methodology has aimed to cover all the lifecycle and to design all the components that characterize Multichannel Adaptive WIS. This paper fills such a gap, by presenting UM-MAIS (Unified Methodology for Multichannel Adaptive Information Systems), a new methodology that capitalizes on well-established existing methods. It supports the analysis and design of the various components of Multichannel Adaptive WISs (including the user's experience) in a comprehensive and unified manner with special emphasis on context modeling, personalization, and adaptation.
Batini, C., Bolchini, D., Ceri, S., Matera, M., Maurino, A., Paolini, P. (2007). The UM-MAIS methodology for multi-channel adaptive web information systems. WORLD WIDE WEB, 10(4), 349-385 [10.1007/s11280-007-0025-x].
The UM-MAIS methodology for multi-channel adaptive web information systems
BATINI, CARLO;MAURINO, ANDREA;
2007
Abstract
Multichannel Adaptive Web Information Systems (WISs) are emerging as a new class of information systems, characterized by their powerful use of mobility and context-awareness. Different methodologies have been proposed so far for the analysis and design of Multichannel Adaptive WISs, specifically focused on the front-end layer or the back-end layer, but no methodology has aimed to cover all the lifecycle and to design all the components that characterize Multichannel Adaptive WIS. This paper fills such a gap, by presenting UM-MAIS (Unified Methodology for Multichannel Adaptive Information Systems), a new methodology that capitalizes on well-established existing methods. It supports the analysis and design of the various components of Multichannel Adaptive WISs (including the user's experience) in a comprehensive and unified manner with special emphasis on context modeling, personalization, and adaptation.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.