An effective approach for mining mobile user habits

International Conference on Information and Knowledge Management, Proceedings

Volumn , Issue , 2010, Pages 1677-1680

  Cao, Huanhuan ^a,b   Bao, Tengfei ^a,b   Yang, Qiang ^c   Chen, Enhong ^a   Tian, Jilei ^b  

^a UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

^b NOKIA RESEARCH CENTER   (United States)

^c HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Hong Kong)

Author keywords

Behavior patterns; Habit mining; Mobile user

Indexed keywords

BEHAVIOR PATTERNS; HABIT MINING; MOBILE USERS; REAL LIFE DATA; USER HABIT; USER INTERACTION;

ASSOCIATION REACTIONS; GLOBAL SYSTEM FOR MOBILE COMMUNICATIONS; KNOWLEDGE MANAGEMENT; MOBILE DEVICES; PORTABLE EQUIPMENT;

BEHAVIORAL RESEARCH;

EID: 78651265934     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1871437.1871702     Document Type: Conference Paper

References (4)

1. Agrawal, R. and Srikant, R. Fast algorithms for mining association rules. In VLDB'94, pages 487-499, 1994.
2. Cao, H., Bao, T., and Yang, Q. et al. An effective approach for mining mobile user habits. Technical report, 2009. http://dm.ustc.edu.cn/paperlist.html
3. Han, J., Pei, J., and Yin, Y. Mining frequent patterns without candidate generation. In SIGMOD'00, pages 1-12. ACM, 2000.
4. Park, J. S., Chen, M., and Yu, P. S. An effective hash-based algorithm for mining association rules. In SIGMOD '95, pages 175-186, 1995.