Enabling large-scale human activity inference on smartphones using Community Similarity Networks (CSN)

UbiComp'11 - Proceedings of the 2011 ACM Conference on Ubiquitous Computing

Volumn , Issue , 2011, Pages 355-364

  Lane, Nicholas D ^a,b,c   Xu, Ye ^a,b,c   Lu, Hong ^a,b,c   Hu, Shaohan ^a,b,c   Choudhury, Tanzeem ^a,b,c   Campbell, Andrew T ^a,b,c   Zhao, Feng ^a,b,c  

^a DARTMOUTH COLLEGE   (United States)

^b Department of Obstetrics Gynecology   (United States)

^c MICROSOFT RESEARCH ASIA   (China)

Author keywords

activity recognition; community learning; mobile phone sensing

Indexed keywords

ACTIVITY RECOGNITION; BEHAVIORAL PATTERNS; CLASSIFICATION MODELS; CLASSIFIER TRAINING; COMMUNITY LEARNING; COMMUNITY SIMILARITY; CONVENTIONAL APPROACH; EMERGING APPLICATIONS; HUMAN ACTIVITIES; MOBILE APPLICATIONS; MOBILE SENSING; POPULATION DIVERSITY; SIMILARITY MEASUREMENTS; SIMILARITY NETWORK; SMARTPHONES;

HUMAN COMPUTER INTERACTION; SALINITY MEASUREMENT; SENSORS; TELECOMMUNICATION EQUIPMENT;

UBIQUITOUS COMPUTING;

EID: 80054061029     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2030112.2030160     Document Type: Conference Paper

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