Using decision-theoretic experience sampling to build personalized mobile phone interruption models

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

Volumn 6696 LNCS, Issue , 2011, Pages 170-187

  Rosenthal, Stephanie ^a   Dey, Anind K ^a   Veloso, Manuela ^a  

^a CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

interruptibility; machine learning; mobile devices; preference elicitation

Indexed keywords

DECISION-THEORETIC; EXPERIENCE SAMPLING; INTERRUPTIBILITY; MACHINE-LEARNING; PREFERENCE ELICITATION; TURN OFFS;

COSTS; MOBILE DEVICES; UBIQUITOUS COMPUTING; LEARNING SYSTEMS;

TELEPHONE SETS;

EID: 79958848075     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-21726-5_11     Document Type: Conference Paper

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