Combining user modeling and machine learning to predict users' multimodal integration patterns

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4299 LNCS, Issue , 2006, Pages 50-62

  Huang, Xiao ^a   Oviatt, Sharon ^a,b   Lunsford, Rebecca ^a,b  

^a Natural Interaction Systems   (United States)

^b OREGON HEALTH AND SCIENCE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EMPIRICAL MODELING; END POINT DETECTION; HETEROGENEOUS USERS; INDIVIDUAL DIFFERENCES; INPUT PATTERNS; LARGE PARTS; LEAVE-ONE-OUT; MACHINE LEARNING TECHNIQUES; MACHINE-LEARNING; MULTI-MODAL; MULTIMODAL INTEGRATION PATTERN; MULTIMODAL SYSTEM; NAIVE-BAYES LEARNING; PERFORMANCE CHARACTERISTICS; PREDICTIVE ACCURACY; SEMANTIC CONSTRAINTS; SIGNAL INPUT; TRAINING STRATEGY; UNIMODAL; USER MODELING; USER-ADAPTIVE;

INTERACTIVE COMPUTER SYSTEMS; LEARNING ALGORITHMS; USER INTERFACES;

LEARNING SYSTEMS;

EID: 77249129013     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11965152_5     Document Type: Conference Paper

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