Find all needed information about Toolkit To Support Intelligibility In Context Aware Applications. Below you can see links where you can find everything you want to know about Toolkit To Support Intelligibility In Context Aware Applications.
https://dl.acm.org/citation.cfm?id=1864353
Context-aware applications should be intelligible so users can better understand how they work and improve their trust in them. However, providing intelligibility is non-trivial and requires the developer to understand how to generate explanations from application decision models.Cited by: 138
https://www.researchgate.net/profile/Anind_Dey/publication/221568578_Toolkit_to_support_intelligibility_in_context-aware_applications/links/02bfe50eaf9c5997c6000000.pdf?disableCoverPage=true
rule-based toolkits for context-aware applications indicates the popularity of rules ( e.g. , [1, 3, 13, 18]). Decision tree classifiers ( e.g. , [35]) learn a tree from a
https://www.researchgate.net/publication/221568578_Toolkit_to_support_intelligibility_in_context-aware_applications
toolkit for building context-aware applications [11, 13] and supports the four most po pular model t ypes (rules, decision trees, naïve Bayes, and hidden Markov models).
https://www.academia.edu/32972888/Toolkit_to_support_intelligibility_in_context-aware_applications
Context-aware applications should be intelligible so users can better understand how they work and improve their trust in them. However, providing intelligibility is non-trivial and requires the developer to understand how to generate explanations
http://www.brianlim.net/wordpress/wp-content/uploads/2010/10/ubicomp2010_demo_poster.pdf
To help users better understand and trust context-aware applications, these applications should be intelligible; they should provide explanations about what they know, and their behavior. We have developed an Intelligibility Toolkit to support the implementation of 8 types of explanations for the 4 most popular decision models used in context-
http://web.cs.wpi.edu/~emmanuel/courses/cs525m/S11/slides/context_toolkit_mary_wk5.pdf
Context Toolkit created by Anind. •Exppg plainer to generate explanations for model-independent types and one Explainer for each of the 4 decision model types. • Reducer to remove explanations that include too many reasons or each reason is too long. • Presenter renders the explanation in form suitable for users. Developers can build
https://ubiquitous.comp.nus.edu.sg/wp-content/uploads/2018/12/lim_mobilehci2011_intelligibility_design.pdf
for a real-world, mobile context-aware prototype. In this work, we focused on intelligibility for the mobile contexts of availability, place, motion, and sound activity. Our contributions are the: 1. Exploration of design and usability issues in making a context-aware application intelligible, and 2.
http://www.brianlim.net/wordpress/wp-content/uploads/2011/04/brianlim-thesis-proposal.pdf
Intelligibility in context-aware applications can improve end-users‘ understanding of how these applications work. Consequently, end-users would learn to trust these applications more, and would also be able to more effectively control these applications. To prove this thesis statement, we approach the problem in three high-level stages.
https://link.springer.com/chapter/10.1007/978-3-319-11206-0_21
Intelligibility is a design principle for context-aware systems which focuses on providing information about context acquisition and interpretation to its users. In this paper we present existing approaches to provide intelligibility and identify a common shortcoming.Cited by: 1
https://link.springer.com/chapter/10.1007%2F978-3-642-39342-6_11
Intelligibility has been proposed to help end-users understand context-aware applications with their complex inference and implicit sensing. Usable explanations can be generated and designed to improve user understanding.Cited by: 6
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