Cross-domain activity recognition

ACM International Conference Proceeding Series

Volumn , Issue , 2009, Pages 61-70

  Zheng, Vincent Wenchen ^a   Hu, Derek Hao ^a   Yang, Qiang ^a  

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

Author keywords

Activity recognition; Crossdomain; Transfer learning; Web search

Indexed keywords

ACTIVITY RECOGNITION; CONFIDENCE LEVELS; CROSS-DOMAIN; FEATURE SPACE; LABELED DATA; REAL-WORLD DATASETS; SENSOR DATA; SIMILARITY FUNCTIONS; SIMILARITY MEASURE; TRANSFER LEARNING; TWO DOMAINS; WEB SEARCHES;

INFORMATION RETRIEVAL; KNOWLEDGE MANAGEMENT; SENSORS; UBIQUITOUS COMPUTING;

WORLD WIDE WEB;

EID: 70450207982     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1620545.1620554     Document Type: Conference Paper

References (30)

1. K. Borgwardt, A. Gretton, M. Rasch, H. Kriegel, B. Schölkopf, and A. Smola. Integrating stuctured biological data by kernel maximum mean discrepancy. In Proc. of the 14th International Conference on Intelligent Systems for Molecular Biology, pages 49-57, 2006.
2. H. H. Bui. A general model for online probabilistic plan recognition. In Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence (IJCAI 2003), pages 1309-1318, 2003.
3. R. Caruana. Multitask learning. Machine Learning, 28(1):41-75, 1997.
4. C.-C. Chang and C.-J. Lin. LIBSVM: a library for support vector machines, 2001.
5. O. Etzioni, M. J. Cafarella, D. Downey, A.-M. Popescu, T. Shaked, S. Soderland, D. S. Weld, and A. Yates. Methods for domain-independent information extraction from the web: An experimental comparison. In Proceedings of the Nineteenth National Conference on Artificial Intelligence (AAAI), pages 391-398, 2004.
6. T. Evgeniou and M. Pontil. Regularized multi-task learning. In Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 109-117, Seattle, Washington, USA, August 2004. ACM.
7. M. R. Hodges and M. E. Pollack. An 'object-use fingerprint': The use of electronic sensors for human identification. In Proceedings of the Ninth International Conference on Ubiquitous Computing (UbiComp 2007), pages 289-303, 2007.
8. D. H. Hu, S. J. Pan, V. W. Zheng, N. N. Liu, and Q. Yang. Real world activity recognition with multiple goals. In Proceedings of the Tenth International Conference on Ubiquitous Computing (UbiComp 2008), pages 30-39, 2008.
9. D. H. Hu and Q. Yang. Cigar: Concurrent and interleaving goal and activity recognition. In Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence (AAAI), pages 1363-1368, 2008.
10. D. H. Hu, X.-X. Zhang, J. Yin, V. W. Zheng, and Q. Yang. Abnormal activity recognition based on hdp-hmm models. In IJCAI, pages 1715-1720, 2009.
11. S. S. Intille, K. Larson, E. M. Tapia, J. Beaudin, P. Kaushik, J. Nawyn, and R. Rockinson. Using a live-in laboratory for ubiquitous computing research. In Proceedings of the Fourth International Conference on Pervasive Computing (Pervasive 2006), pages 349-365, 2006.
12. H. Kautz. A Formal Theory of Plan Recognition. PhD thesis, University of Rochester, 1987.
13. L. Liao. Location-Based Activity Recognition. PhD thesis, University of Washington, 2006.
14. L. Liao, D. Fox, and H. A. Kautz. Learning and inferring transportation routines. In Proceedings of the Nineteenth National Conference on Artificial Intelligence (AAAI), pages 348-353, 2004.
15. C. D. Manning, P. Raghavan, and H. Schutze. Introduction to Information Retrieval. Cambridge University Press, 2008.
16. L. Mihalkova, T. Huynh, and R. J. Mooney. Mapping and revising markov logic networks for transfer learning. In Proceedings of the 22nd AAAI Conference on Artificial Intelligence, pages 608-614, 2007.
17. D. J. Patterson, D. Fox, H. A. Kautz, and M. Philipose. Fine-grained activity recognition by aggregating abstract object usage. In Proceedings of the Ninth IEEE International Symposium on Wearable Computers (ISWC 2005), pages 44-51, 2005.
18. M. Perkowitz, M. Philipose, K. Fishkin, and D. J. Patterson. Mining models of human activities from the web. In Proc. of the 13th international conference on World Wide Web (WWW), pages 573-582, 2004.
19. M. E. Pollack, L. E. Brown, D. Colbry, C. E. McCarthy, C. Orosz, B. Peintner, S. Ramakrishnan, and I. Tsamardinos. Autominder: an intelligent cognitive orthotic system for people with memory impairment. Robotics and Autonomous Systems (RAS), 44(3-4):273-282, 2003.
20. M. Porter. An algorithm for suffix stripping. Program, 14(3):130-137, 1980.
21. R. Raina, A. Battle, H. Lee, B. Packer, and A. Y. Ng. Self-taught learning: Transfer learning from unlabeled data. In Proceedings of the 24th International Conference on Machine Learning, pages 759-766, Corvalis, Oregon, USA, June 2007.
22. M. Sugiyama, S. Nakajima, H. Kashima, P. V. Buenau, and M. Kawanabe. Direct importance estimation with model selection and its application to covariate shift adaptation. In Advances in Neural Information Processing Systems 20. MIT Press, 2008.
23. E. M. Tapia, T. Choudhury, and M. Philipose. Building reliable activity models using hierarchical shrinkage and mined ontology. In Pervasive, pages 17-32, 2006.
24. E. M. Tapia, S. S. Intille, and K. Larson. Activity recognition in the home using simple and ubiquitous sensors. In Pervasive Computing, pages 158-175, 2004.
25. D. L. Vail, M. M. Veloso, and J. D. Lafferty. Conditional random fields for activity recognition. In Proceedings of the Sixth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2007), pages 1-8, 2007.
26. T. van Kasteren, G. Englebienne, and B. Kröse. Recognizing activities in multiple contexts using transfer learning. In AAAI Fall 2008 Symposium: AI in Eldercare, Washington DC, USA, 2008.
27. T. van Kasteren, A. K. Noulas, G. Englebienne, and B. J. A. Kröse. Accurate activity recognition in a home setting. In UbiComp, pages 1-9, 2008.
28. S. Wang, W. Pentney, and A. maria Popescu. Common sense based joint training of human activity recognizers. In Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI), pages 2237-2242, 2007.
29. D. Wyatt, M. Philipose, and T. Choudhury. Unsupervised activity recognition using automatically mined common sense. In Proceedings, The Twentieth National Conference on Artificial Intelligence (AAAI 2005), pages 21-27, 2005.
30. J. Yin, X. Chai, and Q. Yang. High-level goal recognition in a wireless lan. In Proceedings of the Nineteenth National Conference on Artificial Intelligence (AAAI), pages 578-584, 2004.