Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

User Modeling and Adaptation for Daily RoutinesDiagnostic and Accessibility Based User Modelling

User Modeling and Adaptation for Daily Routines: Diagnostic and Accessibility Based User Modelling [This chapter discusses application driven user modelling by dividing user model applications into two broad categories: to provide access for the user with a device and to derive conclusions about the user. Both imply different requirements and different algorithms. The chapter starts by reviewing user modelling literature. Next, the chapter focuses on a discussion of design work in providing accessible documents to deliver accessible educational materials to students, matched to their needs and the capabilities of the device that they are using, so modelling components need to be considered. Next is a presentation of user models supporting the diagnosis of cognitive states, employing a user model that is expressed as fusion of sensor data. With a baseline created, the system captures sensor data over time and compares it with ‘normal’ pattern, to identify indications of Mild Cognitive Impairment (MCI). Finally, a novel framework for User Models design is shown, dividing user data into static and dynamic types.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

User Modeling and Adaptation for Daily RoutinesDiagnostic and Accessibility Based User Modelling

Part of the Human–Computer Interaction Series Book Series
Editors: Martín, Estefanía; Haya, Pablo A.; Carro, Rosa M.
Carmien, Stefan P.; Cantera, Alberto Martínez
User Modeling and Adaptation for Daily Routines — Jan 22, 2013
Download PDF
28 pages

Loading next page...
 
/lp/springer-journals/user-modeling-and-adaptation-for-daily-routines-diagnostic-and-snmXqw7RrB
Publisher
Springer London
Copyright
© Springer-Verlag London 2013
ISBN
978-1-4471-4777-0
Pages
61 –88
DOI
10.1007/978-1-4471-4778-7_3
Publisher site
See Chapter on Publisher Site

Abstract

[This chapter discusses application driven user modelling by dividing user model applications into two broad categories: to provide access for the user with a device and to derive conclusions about the user. Both imply different requirements and different algorithms. The chapter starts by reviewing user modelling literature. Next, the chapter focuses on a discussion of design work in providing accessible documents to deliver accessible educational materials to students, matched to their needs and the capabilities of the device that they are using, so modelling components need to be considered. Next is a presentation of user models supporting the diagnosis of cognitive states, employing a user model that is expressed as fusion of sensor data. With a baseline created, the system captures sensor data over time and compares it with ‘normal’ pattern, to identify indications of Mild Cognitive Impairment (MCI). Finally, a novel framework for User Models design is shown, dividing user data into static and dynamic types.]

Published: Jan 22, 2013

Keywords: Mild Cognitive Impairment; User Model; Main Block; Virtual Learning Environment; Confidence Indicator

There are no references for this article.