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Information & SimulationInformation & Simulation
FacultyFaculty• Ricardo GutierrezRicardo Gutierrez• Frank ShipmanFrank Shipman• Nancy AmatoNancy Amato• James CaverleeJames Caverlee• Jinxiang ChaiJinxiang Chai• Rick FurutaRick Furuta• Tracy HammondTracy Hammond• Andruid KerneAndruid Kerne• John KeyserJohn Keyser• Scott SchaeferScott Schaefer
Research ProjectsResearch Projects• Real-time swarm algorithms for crowd controlReal-time swarm algorithms for crowd control• Simplifying physically-based simulationsSimplifying physically-based simulations• Adaptive information deliveryAdaptive information delivery• Active chemical sensingActive chemical sensing
Sensing
Storage
Connectivity
Computation
Visualization
Interaction
Modeling
Collaboration
Dataintensive
technologies
Humancentered computing
Core expertise @ TAMU
Information retrievalDigital humanities
User interfacesE-collaboration
Cognitive scienceComputer graphics
Pattern recognitionImage processingAlgorithm designWeb 2.0Sensor networksSecure computing
HumanData
Multi-Application Interest Modeling Multi-Application Interest Modeling for Information Triagefor Information Triage
Work on interest modeling assumes one Work on interest modeling assumes one application or one interest but many applications application or one interest but many applications are involved in information triageare involved in information triage
When applications do share a user model, it is When applications do share a user model, it is with regard to a well-known domain modelwith regard to a well-known domain model
We are generating multi-application interest We are generating multi-application interest models that perform better than single-models that perform better than single-application modelsapplication models(IUI 2006).(IUI 2006).
Need to move theNeed to move thetheory to practice.theory to practice.
Multi-Application Interest Modeling Multi-Application Interest Modeling for Information Triage (2)for Information Triage (2)
Where we are:Where we are:
Multi-Application Interest Modeling Multi-Application Interest Modeling for Information Triage (3)for Information Triage (3)
On-going questions:On-going questions:• How to merge interests across applications?How to merge interests across applications?
Multiple possibilities to explore – clustering based on Multiple possibilities to explore – clustering based on text analysis, clustering based on temporality of user text analysis, clustering based on temporality of user actions, bothactions, both
• How to support human feedback on interest How to support human feedback on interest models?models?
Should users intervene when the model is incorrect? Should users intervene when the model is incorrect? How?How?
• Do visualizations lead to more time on valuable Do visualizations lead to more time on valuable documents and better decisions?documents and better decisions?
Adaptation of Information Delivery Adaptation of Information Delivery based on User’s Mental Statebased on User’s Mental State
Requires:Requires:• Real-time recognition of mental load and Real-time recognition of mental load and
attentionattention• Information delivery techniques to match Information delivery techniques to match
mental statemental state
Experimental ResultsExperimental Results
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02:53 05:46 08:38 11:31 14:24 17:17 20:10 23:02 25:55
Ski
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on
du
ctan
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S)
Time (min:sec)
Stress test (game)Relaxation Relaxation
Sensor development in houseSensor development in house Detection of stress in game playingDetection of stress in game playing
Making Sense of Physiological DataMaking Sense of Physiological DataD
ay
Time(Hour)
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90
100
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8 10 12 14 16 18 20
Polar HRM strap
Embeddedsystem Battery inside
Respiration sensor
Respiration transmitter
Flash memory
Adaptive Support for Analyzing Adaptive Support for Analyzing Sensor DataSensor Data
A mixed-initiative strategyA mixed-initiative strategy• User preferences taken as model constraintsUser preferences taken as model constraints• Underlying pattern recognition engine suggests Underlying pattern recognition engine suggests
potential matchespotential matches