Community-Guided Learning: Exploiting Mobile Sensor Users to Model Human Behavior

Proceedings of the 24th AAAI Conference on Artificial Intelligence, AAAI 2010

Volumn , Issue , 2010, Pages 1600-1606

  Peebles, Daniel ^a   Lu, Hong ^a   Lane, Nicholas D ^a   Choudhury, Tanzeem ^a   Campbell, Andrew T ^a  

^a Dartmouth College   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; CLASSIFICATION (OF INFORMATION); USER PROFILE;

HUMAN BEHAVIORS; LABELED TRAINING DATA; LABELINGS; LEARN+; MOBILE SENSORS; SIMILARITY MEASURE; SPLIT-AND-MERGE; VS OFFICE;

BEHAVIORAL RESEARCH;

EID: 85071782165     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (32)

1. Abdelzaher, T.; Anokwa, Y.; Boda, P.; Burke, J.; Estrin, D.; Guibas, L.; Kansal, A.; Madden, S.; and Reich, J. 2007. Mobiscopes for human spaces. IEEE Pervasive Computing 6:20-29.
2. Bao, L., and Intille, S. S. 2004. Activity recognition from user-annotated acceleration data. In Ferscha, A., and Mattern, F., eds., Pervasive, volume 3001 of Lecture Notes in Computer Science, 1-17. Springer.
3. Bishop, C. M. 2007. Pattern Recognition and Machine Learning (Information Science and Statistics). Springer, 1 edition.
4. Blanke, U., and Schiele, B. 2009. Daily routine recognition through activity spotting. In LoCA'09: Proceedings of the 4th International Symposium on Location and Context Awareness, 192-206. Berlin, Heidelberg: Springer-Verlag.
5. Blum, A. 1998. On-line algorithms in machine learning. In Developments from a June 1996 seminar on Online algorithms, 306-325. London, UK: Springer-Verlag.
6. Burke, J.; Estrin, D.; Hansen, M.; Parker, A.; Ramanathan, N.; Reddy, S.; and Srivastava. 2006. Participatory sensing. In In: Workshop on World-Sensor-Web (WSW): Mobile Device Centric Sensor Networks and Applications.
7. Campbell, A. T.; Eisenman, S. B.; Lane, N. D.; Miluzzo, E.; and Peterson, R. A. 2006. People-centric urban sensing. In WICON'06: Proceedings of the 2nd annual international workshop on Wireless internet, 18. New York, NY, USA: ACM.
8. Choudhury, T.; Borriello, G.; Consolvo, S.; Haehnel, D.; Harrison, B.; Hemingway, B.; Hightower, J.; Klasnja, P.; Koscher, K.; LaMarca, A.; Landay, J. A.; LeGrand, L.; Lester, J.; Rahimi, A.; Rea, A.; and Wyatt, D. 2008. The mobile sensing platform: An embedded system for activity recognition. Appears in IEEE Pervasive Magazine - Special Issue on Activity-Based Computing 7(2):32-41.
9. Dixon, S. 2006. Onset detection revisited. In Proc. of the Int. Conf. on Digital Audio Effects (DAFx-06), 133-137.
10. Fogarty, J.; Hudson, S. E.; Atkeson, C. G.; Avrahami, D.; Forlizzi, J.; Kiesler, S.; Lee, J. C.; and Yang, J. 2005. Predicting human interruptibility with sensors. ACM Trans. Comput.-Hum. Interact. 12(1):119-146.
11. Friedman, J.; Hastie, T.; and Tibshirani, R. 1998. Additive logistic regression: a statistical view of boosting. Annals of Statistics 28:2000.
12. Horvitz, E., and Apacible, J. 2003. Learning and reasoning about interruption. In ICMI'03: Proceedings of the 5th international conference on Multimodal interfaces, 20-27. New York, NY, USA: ACM.
13. Horvitz, E.; Koch, P.; and Apacible, J. 2004. Busybody: creating and fielding personalized models of the cost of interruption. In Proceedings of CSCW'04, 507-510. New York, NY, USA: ACM.
14. Huynh, T.; Blanke, U.; and Schiele, B. 2007. Scalable recognition of daily activities with wearable sensors. In 3rd International Symposium on Location- and Context-Awareness (LoCA).
15. Huynh, T.; Fritz, M.; and Schiele, B. 2008. Discovery of activity patterns using topic models. In UbiComp 2008.
16. Krause, A.; Horvitz, E.; Kansal, A.; and Zhao, F. 2008. Toward community sensing. In Proceedings of IPSN'08. Washington, DC, USA: IEEE Computer Society.
17. Lane, N. D.; Lu, H.; Eisenman, S. B.; and Campbell, A. T. 2008. Cooperative techniques supporting sensor-based people-centric inferencing. In Indulska, J.; Patterson, D. J.; Rodden, T.; and Ott, M., eds., Pervasive, volume 5013 of Lecture Notes in Computer Science, 75-92. Springer.
18. Lester, J.; Choudhury, T.; Kern, N.; Borriello, G.; and Hannaford, B. 2005. A hybrid discriminative/generative approach for modeling human activities. In In Proc. of the International Joint Conference on Artificial Intelligence (IJCAI, 766-772.
19. Lester, J.; Choudhury, T.; and Borriello, G. 2006. A practical approach to recognizing physical activities. In Fishkin, K. P.; Schiele, B.; Nixon, P.; and Quigley, A. J., eds., Pervasive, volume 3968 of Lecture Notes in Computer Science, 1-16. Springer.
20. Li, D.; Sethi, I. K.; Dimitrova, N.; and McGee, T. 2001. Classification of general audio data for content-based retrieval. Pattern Recogn. Lett. 22(5):533-544.
21. Mahdaviani, M., and Choudhury, T. 2007. Fast and scalable training of semi-supervised crfs with application to activity recognition. In In Proc. of the Advances of Neural Information Processing Systems 20 (NIPS 2007).
22. Mckinney, M., and Breebaart, J. 2003. Features for audio and music classification. In Proceedings of the International Symposium on Music Information Retrieval, 151-158.
23. Milligan, G. W., and Cooper, M. C. 1985. An examination of procedures for determining the number of clusters in a data set. Psychometrika 50:159-179.
24. Networks, S. 2008. Website. http://www.sensenetworks.com/.
25. Oza, N. C., and Russell, S. 2001. Online bagging and boosting. In Jaakkola, T., and Richardson, T., eds., Eighth International Workshop on Artificial Intelligence and Statistics, 105-112. Key West, Florida. USA: Morgan Kaufmann.
26. Peltonen, V.; Tuomi, J.; Klapuri, A.; and Jyri. 2002. Computational auditory scene recognition. In In IEEE Intl Conf. on Acoustics, Speech, and Signal Processing, 1941-1944.
27. Scheirer, E., and Slaney, M. 1997. Construction and evaluation of a robust multifeature speech/music discriminator. In ICASSP'97: Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'97)-Volume 2, 1331. Washington, DC, USA: IEEE Computer Society.
28. Stikic, M., and Schiele, B. 2009. Activity recognition from sparsely labeled data using multi-instance learning. In Proceedings of LoCA'09, 156-173. Berlin, Heidelberg: Springer-Verlag.
29. Stikic, M.; Van Laerhoven, K.; and Schiele, B. 2008. Exploring semi-supervised and active learning for activity recognition. In In Proc. of IEEE International Symposium on Wearable Computing.
30. Thad, D. M.; Minnen, D.; Starner, T.; Essa, I.; and Isbell, C. 2006. Discovering characteristic actions from on-body sensor data. In In Proc. of IEEE International Symposium on Wearable Computing, 11-18.
31. Torralba, A., and Murphy, K. P. 2007. Sharing visual features for multiclass and multiview object detection. IEEE Trans. Pattern Anal. Mach. Intell. 29(5):854-869. Senior Member-Freeman, William T.
32. Viola, P., and Jones, M. 2001. Robust real-time object detection. In International Journal of Computer Vision.