Toolkit support for developing and deploying sensor-based statistical models of human situations

Conference on Human Factors in Computing Systems - Proceedings

Volumn , Issue , 2007, Pages 135-144

  Fogarty, James ^a   Hudson, Scott E ^b  

^a UNIVERSITY OF WASHINGTON   (United States)

^b Carnegie Mellon University   (United States)

Author keywords

Context aware computing; Machine learning; Sensor based statistical model; Subtle; Toolkit

Indexed keywords

COMPUTER AIDED SOFTWARE ENGINEERING; LEARNING SYSTEMS; MATHEMATICAL MODELS; SENSOR ARRAYS; STATISTICAL METHODS;

CONTEXT AWARE COMPUTING; SENSOR BASED STATISTICAL MODELS; STATISTICAL MODELS; TOOLKITS;

HUMAN COMPUTER INTERACTION;

EID: 35348834302     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1240624.1240645     Document Type: Conference Paper

References (35)

1. Bailey, B.P., Adamczyk, P.D., Chang, T.Y. and Chilson, N.A. (2006) A Framework for Specifying and Monitoring User Tasks. Computers in Human Behavior, 22(4). 658-708.
2. Begole, J.B., Tang, J.C. and Hill, R. (2003) Rhythm Modeling, Visualizations, and Applications. Proceedings of the ACM Symposium on User Interface Software and Technology (UIST 2003), 11-20.
3. Dey, A.K., Mankoff, J., Abowd, G. and Carter, S. (2002) Distributed Mediation of Ambiguous Context in Aware Environments. Proceedings of the ACM Symposium on User Interface Software and Technology (UIST 2002), 121-130.
4. Dey, A.K., Salber, D. and Abowd, G.D. (2001) A Conceptual Framework and a Toolkit for Supporting the Rapid Prototyping of Context-Aware Applications. Human-Computer Interaction (HCI) Journal, 16(2-4). 97-166.
5. Duda, R.O. and Hart, P.E. (1973) Pattern Classification and Scene Analysis. John Wiley and Sons.
6. Edwards, W.K., Bellotti, V., Dey, A.K. and Newman, M.W. (2003) Stuck in the Middle: The Challenges of User-Centered Design and Evaluation for Infrastructure. Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI 2003), 297-304.
7. Fayyad, U.M. and Irani, K.B. (1993) Multi-Interval Discretization of Continuous Valued Attributes for Classification Learning. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 1022-1027.
8. Fogarty, J., Baker, R.S. and Hudson, S.E. (2005) Case Studies in the use of ROC Curve Analysis for Sensor-Based Estimates in Human Computer Interaction. Proceedings of Graphics Interface (GI 2005), 129-136.
9. Fogarty, J., Hudson, S. and Lai, J. (2004) Examining the Robustness of Sensor-Based Statistical Models of Human Interruptibility. Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI 2004), 207-214.
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 Transactions on Computer-Human Interaction (TOCHI), 12(1). 119-146.
11. Fogarty, J., Ko, A.J., Aung, H.H., Golden, E., Tang, K.P. and Hudson, S.E. (2005) Examining Task Engagement in Sensor-Based Statistical Models of Human Interruptibility. Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI 2005), 331-340.
12. Fogarty, J., Lai, J. and Christensen, J. (2004) Presence versus Availability: The Design and Evaluation of a Context-Aware Communication Client. International Journal of Human-Computer Studies (IJHCS), 61(3). 299-317.
13. Hand, D.J. and Till, R.J. (2001) A Simple Generalisation of the Area Under the ROC Curve for Multiple Class Classification Problems. Machine Learning, 45(2). 171-186.
14. Hanley, J.A. and McNeil, B.J. (1982) The Meaning and Use of the Area Under a Receiver Operating Characteristic (ROC) Curve. Radiology, 143. 29-36.
15. Ho, J. and Intille, S.S. (2005) Using Context-Aware Computing to Reduce the Perceived Burden of Interruptions from Mobile Devices. Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI 2005), 909-918.
16. Horvitz, E. and Apacible, J. (2003) Learning and Reasoning about Interruption. Proceedings of the International Conference on Multimodal Interfaces (ICMI 2003), 20-27.
17. Horvitz, E., Jacobs, A. and Hovel, D. (1999) Attention-Sensitive Alerting. Proceeding of the Conference on Uncertainty and Artificial Intelligence (UAI 1999), 305-313.
18. Horvitz, E., Kadie, C., Paek, T. and Hovel, D. (2003) Models of Attention in Computing and Communication: From Principles to Applications. Communications of the ACM, 46(3). 52-59.
19. Horvitz, E., Koch, P. and Apacible, J. (2004) BusyBody: Creating and Fielding Personalized Models of the Cost of Interruption. Proceedings of the ACM Conference on Computer Supported Cooperative Work (CSCW 2004), 507-510.
20. Horvitz, E., Koch, P., Kadie, C.M. and Jacobs, A. (2002) Coordinate: Probabilistic Forecasting of Presence and Availability. Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI 2002), 224-233.
21. Hsieh, G., Tang, K.P., Hong, J.I. (2007) The Design and Evaluation of Privacy Controls and Feedback Mechanisms for Contextual Instant Messaging. Submitted for Review.
22. Hudson, S.E., Fogarty, J., Atkeson, C.G., Avrahami, D., Forlizzi, J., Kiesler, S., Lee, J.C. and Yang, J. (2003) Predicting Human Interruptibility with Sensors: A Wizard of Oz Feasibility Study. Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI 2003), 257-264.
23. Iqbal, S.T., Adamczyk, P.D., Zheng, X.S. and Bailey, B.P. (2005) Towards an Index of Opportunity: Understanding Changes in Mental Workload During Task Execution. Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI 2005), 311-230.
24. Kern, N. and Schiele, B. (2003) Context-Aware Notification for Wearable Computing. Proceedings of the IEEE International Symposium on Wearable Computing (ISWC 2003), 223-230.
25. Kohavi, R. and John, G.H. (1997) Wrappers for Feature Subset Selection. Artificial Intelligence, 97(1-2). 273-324.
26. LaMarca, A., Chawathe, Y., Consolvo, S., Hightower, J., Smith, I., Scott, J., Sohn, T., Howard, J., Hughes, J., Potter, F., Tabert, J., Powledge, P., Borriello, G. and Schilit, B.N. (2005) Place Lab: Device Positioning Using Radio Beacons in the Wild. Proceedings of the International Conference on Pervasive Computing (Pervasive 2005), 116-133.
27. Langley, P. and Sage, S. (1994) Induction of Selected Bayesian Classifiers. Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI 1994), 399-406.
28. Lu, L., Zhang, H. and Jiang, H. (2002) Content Analysis for Audio Classification and Segmentation. IEEE Transactions on Speech and Audio Processing, 10(7). 504-516.
29. Markovitch, S. and Rosenstein, D. (2002) Feature Generation Using General Constructor Functions. Machine Learning, 49(1). 59-98.
30. Mitchell, T.M. (1997) Machine Learning. McGraw-Hill.
31. Nagel, K.S., Hudson, J.M. and Abowd, G. (2004) Predictors of Availability in Home Life Context-Mediated Communication. Proceedings of the ACM Conference on Computer Supported Cooperative Work (CSCW 2004), 497-506.
32. Quinlan, J.R. (1993) C4.5: Programs for Machine Learning. Morgan Kaufmann.
33. Tullio, J., Dey, A.K., Chalecki, J. and Fogarty, J. (2007) How it Works: A Field Study of Non-Technical Users Interacting with an Intelligent System. ACM Conference on Human Factors in Computing Systems (CHI 2007), To Appear.
34. Witten, I.H. and Frank, E. (1999) Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. Morgan Kaufmann.
35. Yu, L. and Liu, H. (2003) Feature Selection for High-Dimensional Data: A Fast Correlation-Based Filter Solution. The International Conference on Machine Learning (ICML 2003), 856-863.