fast and robust interface generation for ubiquitous ...kgajos/papers/2005/kgajos-ubicomp… ·...
TRANSCRIPT
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Fast And Robust Interface Generation for Ubiquitous
ApplicationsThe SUPPLE Project
University of Washington, Seattle
Krzysztof Gajos, David Christianson, Raphael Hoffmann, Tal Shaked, Kiera Henning,
Jing Jing Long, and Daniel S. Weld
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Fast And Robust Interface Generation for Ubiquitous
Applications
Automatic, On The Fly
The SUPPLE ProjectUniversity of Washington, Seattle
Krzysztof Gajos, David Christianson, Raphael Hoffmann, Tal Shaked, Kiera Henning,
Jing Jing Long, and Daniel S. Weld
![Page 3: Fast And Robust Interface Generation for Ubiquitous ...kgajos/papers/2005/kgajos-ubicomp… · Applications Automatic, On The Fly The SUPPLE Project University of Washington, Seattle](https://reader034.vdocument.in/reader034/viewer/2022050201/5f5465801cd521345f258cec/html5/thumbnails/3.jpg)
Motivation
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Motivation
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Motivation
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Motivation
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Motivation
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Motivation
• Variety of display devices & interaction contexts makes hand-designed interfaces expensive⇒ Adapt to device characteristics
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Motivation
• Variety of display devices & interaction contexts makes hand-designed interfaces expensive⇒ Adapt to device characteristics
• Current interfaces: complex & “One size fits all” ⇒ Adapt to users and tasks
![Page 10: Fast And Robust Interface Generation for Ubiquitous ...kgajos/papers/2005/kgajos-ubicomp… · Applications Automatic, On The Fly The SUPPLE Project University of Washington, Seattle](https://reader034.vdocument.in/reader034/viewer/2022050201/5f5465801cd521345f258cec/html5/thumbnails/10.jpg)
Motivation
• Variety of display devices & interaction contexts makes hand-designed interfaces expensive⇒ Adapt to device characteristics
• Current interfaces: complex & “One size fits all” ⇒ Adapt to users and tasks
⇒ Automatic interface generation is a scalable
solution
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Approach
• Develop abstract representation for:
• Interfaces
• Display devices
• Users
• Automatically generate interfaces from the abstractions
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SUPPLE Architecture
Display
Device Model
Target Device
SUPPLEInterface Model
Applicationor
Appliance
User Model
User's InfoSpace
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SUPPLE Architecture
Display
Device Model
Target Device
SUPPLEInterface Model
Applicationor
Appliance
User Model
User's InfoSpace
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Road MapMotivationModeling user interfaces in SUPPLE
User interface generation as optimizationAutomatically adapting user interfaces
A preliminary user studyAdaptation in SUPPLE
Customization support in SUPPLE
Conclusions
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• simple types:
• media types:
• containers:
• derivative types:
• vectors:
• actions: !1 ! !2
!!, C! "
Modeling User Interfaces
vector(!)
i nt| f loat|st r i ng|bool
{!ii!1...n}
image|interactiveMap
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Modeling User Interfaces
Light Level: τ: <int, [0,10]>
Power: τ: bool
Light: τ: { , }
Light Bank: τ: { , , }
Light ... Light ...
A/V: τ: { , }
Projector: τ: { , }
Classroom:τ: { , , }
Input:τ: <string, {data1,data2, video}>
Vent:τ: <int, [0,3]>
Power: τ : bool
Screen:τ: bool
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Modeling User Interfaces
Light Level: τ: <int, [0,10]>
Power: τ: bool
Light: τ: { , }
Light Bank: τ: { , , }
Light ... Light ...
A/V: τ: { , }
Projector: τ: { , }
Classroom:τ: { , , }
Input:τ: <string, {data1,data2, video}>
Vent:τ: <int, [0,3]>
Power: τ : bool
Screen:τ: bool
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Light Level:
!: <int, [0,10]>Power:
!: bool
Light:
!: { , }
Light Bank:
!: { , , }
Light ... Light ...
A/V:
!: { , }
Projector:
!: { , }
Classroom:
!: { , , }
Input:
!: <string, {data1,data2, video}>Vent:
!: <int, [0,3]>Power:
! : boolScreen:
!: bool
Modeling User Interfaces
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Model (UI, Device, User) - Algorithm - Results - Personalization (Adaptation, Customization) - Arnauld - Consistency - Task Models
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Model (UI, Device, User) - Algorithm - Results - Personalization (Adaptation, Customization) - Arnauld - Consistency - Task Models
Click!
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Model (UI, Device, User) - Algorithm - Results - Personalization (Adaptation, Customization) - Arnauld - Consistency - Task Models
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Model (UI, Device, User) - Algorithm - Results - Personalization (Adaptation, Customization) - Arnauld - Consistency - Task Models
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Model (UI, Device, User) - Algorithm - Results - Personalization (Adaptation, Customization) - Arnauld - Consistency - Task Models
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Model (UI, Device, User) - Algorithm - Results - Personalization (Adaptation, Customization) - Arnauld - Consistency - Task Models
Click!
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Model (UI, Device, User) - Algorithm - Results - Personalization (Adaptation, Customization) - Arnauld - Consistency - Task Models
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Model (UI, Device, User) - Algorithm - Results - Personalization (Adaptation, Customization) - Arnauld - Consistency - Task Models
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Media Types
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Subtyping
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Subtyping
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Subtyping
Click!
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Road MapMotivationModeling user interfaces in SUPPLE
User interface generation as optimizationAutomatically adapting user interfaces
A preliminary user studyAdaptation in SUPPLE
Customization support in SUPPLE
Conclusions
![Page 36: Fast And Robust Interface Generation for Ubiquitous ...kgajos/papers/2005/kgajos-ubicomp… · Applications Automatic, On The Fly The SUPPLE Project University of Washington, Seattle](https://reader034.vdocument.in/reader034/viewer/2022050201/5f5465801cd521345f258cec/html5/thumbnails/36.jpg)
Model (UI, Device, User) - Algorithm - Results - Personalization (Adaptation, Customization) - Arnauld - Consistency - Task Models
User Interface Generation as Optimization
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Model (UI, Device, User) - Algorithm - Results - Personalization (Adaptation, Customization) - Arnauld - Consistency - Task Models
• Driven by a Cost function ($) -- estimated user effort to manipulate a rendering of the interface
User Interface Generation as Optimization
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Model (UI, Device, User) - Algorithm - Results - Personalization (Adaptation, Customization) - Arnauld - Consistency - Task Models
• Driven by a Cost function ($) -- estimated user effort to manipulate a rendering of the interface
• Cost function derived from device model
User Interface Generation as Optimization
![Page 39: Fast And Robust Interface Generation for Ubiquitous ...kgajos/papers/2005/kgajos-ubicomp… · Applications Automatic, On The Fly The SUPPLE Project University of Washington, Seattle](https://reader034.vdocument.in/reader034/viewer/2022050201/5f5465801cd521345f258cec/html5/thumbnails/39.jpg)
Model (UI, Device, User) - Algorithm - Results - Personalization (Adaptation, Customization) - Arnauld - Consistency - Task Models
• Driven by a Cost function ($) -- estimated user effort to manipulate a rendering of the interface
• Cost function derived from device model
• Algorithm: branch-and-bound search with full constraint propagation at each step
User Interface Generation as Optimization
![Page 40: Fast And Robust Interface Generation for Ubiquitous ...kgajos/papers/2005/kgajos-ubicomp… · Applications Automatic, On The Fly The SUPPLE Project University of Washington, Seattle](https://reader034.vdocument.in/reader034/viewer/2022050201/5f5465801cd521345f258cec/html5/thumbnails/40.jpg)
Model (UI, Device, User) - Algorithm - Results - Personalization (Adaptation, Customization) - Arnauld - Consistency - Task Models
• Driven by a Cost function ($) -- estimated user effort to manipulate a rendering of the interface
• Cost function derived from device model
• Algorithm: branch-and-bound search with full constraint propagation at each step
• Performance: 0.2 - 2.0 seconds on a desktop computer
User Interface Generation as Optimization
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Model (UI, Device, User) - Algorithm - Results - Personalization (Adaptation, Customization) - Arnauld - Consistency - Task Models
• Driven by a Cost function ($) -- estimated user effort to manipulate a rendering of the interface
• Cost function derived from device model
• Algorithm: branch-and-bound search with full constraint propagation at each step
• Performance: 0.2 - 2.0 seconds on a desktop computer
User Interface Generation as Optimization
![Page 42: Fast And Robust Interface Generation for Ubiquitous ...kgajos/papers/2005/kgajos-ubicomp… · Applications Automatic, On The Fly The SUPPLE Project University of Washington, Seattle](https://reader034.vdocument.in/reader034/viewer/2022050201/5f5465801cd521345f258cec/html5/thumbnails/42.jpg)
User Interface Generation as Optimization
• Flexible with respect to screen size
• Versatile: Same algorithm for different devices
• Allows new concerns to be included in the rendering process, e.g.:
• Cross-device consistency
• Adaptation to usage patterns
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Robustly Adapting to Different Screen Sizes
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Robustly Adapting to Different Screen Sizes
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Robustly Adapting to Different Screen Sizes
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Single Algorithm -- Many Devices
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Single Algorithm -- Many Devices
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Single Algorithm -- Many Devices
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Single Algorithm -- Many Devices
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Single Algorithm -- Many Devices
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Adapting To Usage Patterns
SUPPLE with an empty
trace
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Adapting To Usage Patterns
SUPPLE with an empty
trace
SUPPLE with a “lights-heavy”
trace
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Road MapMotivationModeling user interfaces in SUPPLE
User interface generation as optimizationAutomatically adapting user interfaces
A preliminary user studyAdaptation in SUPPLE
Customization support in SUPPLE
Conclusions
![Page 54: Fast And Robust Interface Generation for Ubiquitous ...kgajos/papers/2005/kgajos-ubicomp… · Applications Automatic, On The Fly The SUPPLE Project University of Washington, Seattle](https://reader034.vdocument.in/reader034/viewer/2022050201/5f5465801cd521345f258cec/html5/thumbnails/54.jpg)
Adapting To Usage Patterns By Complete Makeover
SUPPLE with an empty
trace
SUPPLE with a “lights-heavy”
trace
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Adapting To Usage Patterns By Complete Makeover
SUPPLE with an empty
trace
SUPPLE with a “lights-heavy”
trace
Is this the only way to adapt?
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Content Eliding
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Content Eliding
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Content Eliding
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Content Eliding
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Visual Popout
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Visual Popout
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Split Interfaces
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Split Interfaces
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Split Interfaces
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Adaptation StrategiesEfficiency
Confusion
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Adaptation StrategiesEfficiency
Confusion
Efficiency
Confusion
Complete
Makeover
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Adaptation StrategiesEfficiency
Confusion
Complete
Makeover
Content eliding
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Adaptation StrategiesEfficiency
Confusion
Visual Popout
Complete
Makeover
Content eliding
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Adaptation StrategiesEfficiency
Confusion
Split
Visual Popout
Complete
Makeover
Content eliding
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Adaptation StrategiesEfficiency
Confusion
Split
Visual Popout
Complete
Makeover
Content eliding
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Preliminary User Study
Split Interface
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Preliminary User Study
Split Interface
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Preliminary User Study
Split Interface
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Preliminary User Study
Split Interface
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Preliminary User Study
Split Interface
Visual Popout
Interface
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Preliminary User Study Results
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Preliminary User Study Results
• Split Interface strongly preferred over non-adaptive
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Preliminary User Study Results
• Split Interface strongly preferred over non-adaptive
• Both adaptive interfaces slightly faster than non-adaptive
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Preliminary User Study Results
• Split Interface strongly preferred over non-adaptive
• Both adaptive interfaces slightly faster than non-adaptive
• But: Visual Popout interface often found distracting
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Sneak Peak: Followup Study
with Mary Czerwinski and Desney Tan
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Sneak Peak: Followup Study
• In a different setting, we tested three adaptation strategies including Split Interface and Visual Popout Interface
with Mary Czerwinski and Desney Tan
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Sneak Peak: Followup Study
• In a different setting, we tested three adaptation strategies including Split Interface and Visual Popout Interface
• Users strongly preferred and were significantly faster using Split Interface
with Mary Czerwinski and Desney Tan
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Sneak Peak: Followup Study
• In a different setting, we tested three adaptation strategies including Split Interface and Visual Popout Interface
• Users strongly preferred and were significantly faster using Split Interface
• Users strongly disliked Visual Popout Interface
with Mary Czerwinski and Desney Tan
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Split Interfaces in SUPPLE
• Adapting by promoting hard-to-reach but frequently used functionality
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Split Interfaces in SUPPLE
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Click!
Split Interfaces in SUPPLE
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Split Interfaces in SUPPLE
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Click!
Split Interfaces in SUPPLE
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Click!
Split Interfaces in SUPPLE
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Click!
Click!
Split Interfaces in SUPPLE
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Split Interfaces in SUPPLE
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Click!
Split Interfaces in SUPPLE
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Split Interfaces in SUPPLE
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Split Interfaces in SUPPLE
Four extra clicks required just to print in
landscape mode!
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Split Interfaces in SUPPLE
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Split Interfaces in SUPPLE
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Split Interfaces in SUPPLE
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System- Vs. User-Initiated Adaptation: Customization
• Customizing any part of the interface with drag and drop
• Out of order undo
• Generalization
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Customization
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Customization
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Customization
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Customization
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Customization
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Customization
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Road MapMotivationModeling user interfaces in SUPPLE
User interface generation as optimizationAutomatically adapting user interfaces
A preliminary user studyAdaptation in SUPPLE
Customization support in SUPPLE
Conclusions
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Conclusions
• A powerful, flexible and practical tool for automatically generating user interfaces for multiple devices
• Adaptation and customization offer the possibility of creating custom-made UIs for each user
• Support for distributed operation and caching makes it practical even on small devices
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Can I Have It?
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Can I Have It?
• We are awaiting permission to release SUPPLE as an open source toolkit
• Visit SUPPLE web site to sign up for the user’s mailing list
Yes!
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Contributors
Daniel Weld Raphael Hoffmann
Kiera Henning Jing Jing Long meAnthony Wu
Dave Christianson Tal Shaked
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More Information
• SUPPLE:http://www.cs.washington.edu/ai/supple/ : supple interfaces
• Krzysztof Gajos: [email protected]
• Daniel Weld: [email protected]
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• SUPPLE:http://www.cs.washington.edu/ai/supple/ : supple interfaces
• Krzysztof Gajos: [email protected]
• Daniel Weld: [email protected]
More Information