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Supporting Adaptive Interfaces in a Knowledge-Based User Interface Environment. Piyawadee Noi Sukaviriya James Foley. Piyawadee Noi Sukaviriya. was a Research Scientist II at Georgia Institute of Technology doctoral degree from the George Washington University

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supporting adaptive interfaces in a knowledge based user interface environment

Supporting Adaptive Interfaces in a Knowledge-Based User Interface Environment

Piyawadee Noi Sukaviriya

James Foley

piyawadee noi sukaviriya
Piyawadee Noi Sukaviriya
  • was a Research Scientist II at Georgia Institute of Technology
  • doctoral degree from the George Washington University
  • Mobile Solutions/Personal SystemsIBM Thomas J Watson Research Center CHI \'97 Workshop: Speech User Interface Design Challenges
james foley
James Foley
  • Associate Dean, College of Computing Georgia Institute of Technology
  • chairman of the Computing Research Association
user interface design environment
User Interface Design Environment
  • Adaptive Interface
  • User Model
  • Adaptation Strategy
basic construct of user model
Basic Construct of User Model
  • Using one interaction technique
  • How many successful uses
  • User cancels, requests help => difficulties
  • Which technique used to perform action
  • Repeated patterns
  • How long the user spends on each help session
  • Assumes technique used frequently is the preferred technique
adaptation strategy
Adaptation Strategy
  • Suggestions; user has control
  • Reorganizations made less frequently
daniel crow
Daniel Crow
  • School of Computer Studies – University of Leeds
  • Pattern identification and machine learning in human-computer interaction
barbara smith
Barbara Smith
  • Professor - University of Huddersfield, West Yorkshire, U.K.
  • Interested in constraint programming and related fields of AI, specifically in Algorithms, Problems and Empirical Studies
task oriented interfaces
Task-Oriented Interfaces
  • DB_Habits – adaptive interface system
  • Uses command sequences
  • Use small amounts of low-level system knowledge
  • Adaptive - individual modelling with descriptive methods
  • Malleable – adaptation to individual user
  • Collaborative – interface as bridge between 2 agents
user modelling
User Modelling
  • Pattern recognition
  • Assumption: repeated sequences rep. tasks
  • Collaborative dialogue to confirm “task”
  • Identify equivalent commands in logfile
  • Fit between patterns and tasks
  • Pattern freqency
  • Order of tool usage
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