An unsupervised framework for sensing individual and cluster behavior patterns from human mobile data

UbiComp'12 - Proceedings of the 2012 ACM Conference on Ubiquitous Computing

Volumn , Issue , 2012, Pages 153-162

  Zheng, Jiangchuan ^a   Ni, Lionel M ^a,b  

^a Department of Computer Science and Engineering ^*  (Hong Kong)

^b HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Graphical models; Human activity inference; Human behavior learning; Mobile phone sensing

Indexed keywords

BEHAVIOR PATTERNS; DAILY LIVES; DATA SETS; DATA SPARSITY PROBLEMS; GRAPHICAL MODEL; HUMAN ACTIVITIES; HUMAN BEHAVIOR UNDERSTANDING; HUMAN BEHAVIORS; INFORMATION SHARING; MOBILE DATA; MULTIPLE USER; PROBABILISTIC FRAMEWORK; REALITY MININGS; SINGLE USERS; UBIQUITOUS APPLICATION; USER ACTIVITY;

E-LEARNING; SOCIAL SCIENCES; UBIQUITOUS COMPUTING;

BEHAVIORAL RESEARCH;

EID: 84867439746     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2370216.2370241     Document Type: Conference Paper

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