Why-oriented end-user debugging of naive Bayes text classification

ACM Transactions on Interactive Intelligent Systems

Volumn 1, Issue 1, 2011, Pages

  Kulesza, Todd ^a   Stumpf, Simone ^b   Wong, Weng Keen ^a   Burnett, Margaret M ^a   Perona, Stephen ^a   Ko, Andrew ^c   Oberst, Ian ^a  

^a OREGON STATE UNIVERSITY   (United States)

^b CITY UNIVERSITY   (United Kingdom)

^c UNIVERSITY OF WASHINGTON   (United States)

Author keywords

Debugging; End user programming; Machine learning

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTER DEBUGGING; COMPUTER PROGRAMMING; FORECASTING; INFORMATION SCIENCE;

END USER PROGRAMMING; EXPLORATORY STUDIES; HANDWRITING RECOGNITION; INTELLIGENT ASSISTANTS; LIMITED ATTENTIONS; MACHINE LEARNING TECHNIQUES; STATISTICAL MACHINE LEARNING; TEXT CLASSIFICATION;

LEARNING SYSTEMS;

EID: 84983579946     PISSN: 21606455     EISSN: 21606463     Source Type: Journal    
DOI: 10.1145/2030365.2030367     Document Type: Article

References (47)

1. BANDURA, A. 1977. Self-efficacy: Toward a unifying theory of behavioral change. Psych. Rev. 8, 2, 191-215.
2. BECKER, B., KOHAVI, R., AND SOMMERFIELD, D. 2001. Visualizing the simple Bayesian classifier. In Information Visualization in Data Mining and Knowledge Discovery, U. Fayyad et al. Eds., 237-249.
3. BECKWITH, L., BURNETT, M.,WIEDENBECK, S., COOK, C., SORTE, S., AND HASTINGS, M. 2005. Effectiveness of enduser debugging software features: Are there gender issues? In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. 869-878.
4. BECKWITH, L. 2007. Gender HCI issues in end-user programming. Ph.D. dissertation, Oregon StateUniversity, Corvallis, OR.
5. BURNETT, M., COOK, C., PENDSE, O., ROTHERMEL, G., SUMMET, J., AND WALLACE, C. 2003. End-user software engineering with assertions in the spreadsheet paradigm. In Proceedings of the 25 International Conference of Software Engineering. 93-103.
6. CARROLL, J. AND ROSSON, M. 1987. Paradox of the active user. In Interfacing Thought: Cognitive Aspects of Human-Computer Interaction, J. Carroll Ed., MIT Press, Cambridge, MA, 80-111.
7. CHAN, H. AND DARWICHE, A. 2004. Sensitivity analysis in Bayesian networks: from single to multiple parameters. In Proceedings of the 20th Conference on Uncertainty in Artificial Intelligence. 67-75.
8. CHAN, H. AND DARWICHE, A. 2002. When do numbers really matter? J. Artif. Intell. Res.17, 265-287.
9. CHEN, J. AND WELD, D. S. 2008. Recovering from errors during programming by demonstration. In Proceedings of the 13th International Conference on Intelligent User Interfaces. 159-168.
10. COHEN, W. 1996. Learning rules that classify e-mail. In Proceedings of the AAAI Spring Symposium on Machine Learning.
11. COMPEAU, D. AND HIGGINS, C. 1995. Application of social cognitive theory to training for computer skills. Inf. Syst. Res. 6, 2, 118-143.
12. DAVIES, S. P. 1996. Display-based problem solving strategies in computer programming. In Proceedings of the 6th Workshop for Empirical Studies of Programmers. 59-76.
13. GLASS, A., MCGUINNESS, D., AND WOLVERTON, M. 2008. Toward establishing trust in adaptive agents. In Proceedings of the 13th International Conference on Intelligent User Interfaces. 227-236.
14. GRIGOREANU, V., CAO, J., KULESZA, T., BOGART, C., RECTOR, K., BURNETT, M., AND WIEDENBECK, S. 2008. Can feature design reduce the gender gap in end-user software development environments? In Proceedings of Visual Learning and Human-Centric Computing. 149-156.
15. GUYON, I. AND ELISSEEFF, A. 2003. An introduction to variable and feature selection. J. Mach. Learn. Res. 3, 1157-1182.
16. HASTIE, T., TIBSHIRANI, R., AND FRIEDMAN, J. H. 2003. The Elements of Statistical Learning. Springer, Berlin.
17. KAPOOR, A., LEE, B., TAN, D., AND HORVITZ, H. 2010. Interactive optimization for steeringmachine classification. In Proceedings of the Annual Conference on Human Factors in Computing Systems. 1343-1352.
18. KISSINGER, C., BURNETT, M., STUMPF, S., SUBRAHMANIYAN, N., BECKWITH, L., YANG, S., AND ROSSON, M. B. 2006. Supporting end-user debugging:What do users want to know?. In Proceedings of the Working Conference on Advanced Visual Interfaces. 135-142.
19. KO, A. J. 2008. Asking and answering questions about the causes of software behaviors. Ph.D. dissertation; Tech. rep.CMU-CS-08-122, Human-Computer Interaction Institute, Carnegie Mellon University.
20. KO, A. J.,MYERS, B., AND AUNG, H. 2004. Six learning barriers in end-user programming systems. In Proceedings of Visual learning and Human-Centric Computing. 199-206.
21. KONONENKO, I. 1993. Inductive and Bayesian learning in medical diagnosis. Appl. Artif. Intell. 7, 317-337.
22. KULESZA, T.,WONG, W., STUMPF, S., PERONA, S.,WHITE, R., BURNETT, M. M.,OBERST, I., AND KO, A. J. 2009. Fixing the program my computer learned: Barriers for end users, challenges for the machine. In Proceedings of the 14th International Conference on Intelligent User Interfaces. 187-196.
23. LACAVE, C. AND DIEZ, F. 2002. A review of explanation methods for Bayesian networks. Knowl. Eng. Rev. 17, 2, 107-127.
24. LIEBERMAN, H. (ED.) 2001. Your Wish is My Command: Programming By Example. Morgan Kaufmann.
25. LIM, B. Y., DEY, A. K., AND AVRAHAMI, D. 2009. Why and why not explanations improve the intelligibility of context-aware intelligent systems. In Proceedings of the Annual Conference on Human Factors in Computing Systems. 2119-2128.
26. LIM, B. Y. AND DEY, A. K. 2009. Assessing demand for intelligibility in context-aware applications. In Proceedings of the 11th International Conference on Ubiquitous Computing. 195-204.
27. LITTLE, G., LAU, T., CYPHER, A., LIN, J., HABER, E., AND KANDOGAN, E. 2007. Koala: Capture, share, automate, personalize business processes on the web. In Proceedings of the Annual Conference on Human Factors in Computing Systems. 943-946.
28. LIU, H., LIEBERMAN, H., AND SELKER, T. 2003. A model of textual affect sensing using real-world knowledge. In Proceedings of the International Conference on Intelligent User Interfaces. 125-132.
29. MARON, M. E. 1961. Automatic indexing: An experimental inquiry. J. ACM 8, 3, 404-417.
30. MCDANIEL, R. AND MYERS, B. 1999. Getting more out of programming-by- demonstration. In Proceedings of the Conference on Human Factors in Computing Systems. 442-449.
31. MEYERS-LEVY, J. 1989. Gender differences in information processing: A selectivity interpretation. Cognitive and Affective Responses to Advertising, P. Cafferata and A. Tybout Eds., Lexington Books.
32. MYERS, B., WEITZMAN, D., KO, A. J., AND CHAU, D. H. 2006. Answering why and why not questions in user interfaces. In Proceedings of the Conference on Human Factors in Computing Systems. 397-406.
33. NG, A. Y. AND JORDAN, M. I. 2002. On discriminative vs generative classifiers: A comparison of logistic regression and naïve Bayes. Advances Neural Inf. Process. Syst. 14, 841-848.
34. PATEL, K., FOGARTY, J., LANDAY, J., AND HARRISON, B. 2008. Investigating statistical machine learning as a tool for software development. In Proceedings of the Annual SIGCHI Conference on Human Factors in Computing Systems. 667-676.
35. POULIN, B., EISNER, R., SZAFRON, D., LU, P., GREINER, R.,WISHART, D. S., FYSHE, A., PEARCY, B., MACDONELL, C., AND ANVIK, J. 2006. Visual explanation of evidence in additive classifiers. In Proceedings of the AAAI Spring Symposium. 1822-1829.
36. RUSSELL, S. J. AND NORVIG, P. 2003. Artificial Intelligence: A Modern Approach. Prentice Hall, Upper Saddle River, NJ.
37. STUMPF, S.,RAJARAM, V.,LI, L.,BURNETT, M.,DIETTERICH, T.,SULLIVAN, E.,DRUMMOND, R., AND HERLOCKER, J. 2007. Toward harnessing user feedback for machine learning. In Proceedings of the International Conference on Intelligent User Interfaces. 82-91.
38. STUMPF, S., SULLIVAN, E., FITZHENRY, E., OBERST, I.,WONG, W.-K., AND BURNETT, M. 2008. Integrating rich user feedback into intelligent user interfaces. In Proceedings of the International Conference on Intelligent User Interfaces. 50-59.
39. STUMPF, S., RAJARAM, V., LI, L.,WONG, W.-K., BURNETT, M.,DIETTERICH, T., SULLIVAN, E., AND HERLOCKER, J. 2009. Interacting meaningfully with machine learning systems: Three experiments. Int. J. Human-Comput. Stud. 67, 8, 639-662.
40. SUBRAHMANIYAN, N., KISSINGER, C., RECTOR, K., INMAN, D., KAPLAN, J., BECKWITH, L., AND BURNETT, M. 2007. Explaining debugging strategies to end-user programmers. In Proceedings of the Visual Learning and Human- Centric Computing. 127-136.
41. SUBRAHMANIYAN, N., BECKWITH, L., GRIGOREANU, V., BURNETT, M., WIEDENBECK, S., NARAYANAN, V., BUCHT, K., DRUMMOND, R., AND FERN, X. 2008. Testing vs. code inspection vs. ... what else? Male and female end users' debugging strategies. In Proceedings of the 26th Annual SIGCHI Conference on Human Factors in Computing Systems. 617-626.
42. TALBOT, J., LEE, B.,KAPOOR, A., AND TAN, D. S. 2009. EnsembleMatrix: Interactive visualization to support machine learning with multiple classifiers. In Proceedings of the 27th International Conference on Human Factors in Computing Systems. 1283-1292.
43. TULLIO, J., DEY, A., CHALECKI, J., AND FOGARTY, J. 2007. How it works: A field study of nontechnical users interacting with an intelligent system. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. 31-40.
44. UNGAR, D., LIEBERMAN, H., AND FRY, C. 1997. Debugging and the experience of immediacy. Comm. ACM 40, 4, 38-43.
45. VANDER ZANDEN, B. AND MYERS, B. 1995. Demonstrational and constraint-based techniques for pictorially specifying application objects and behaviors. ACM Trans. Comput.-Human Interac. 2, 4, 308-356.
46. WAGNER, E. AND LIEBERMAN, H. 2004. Supporting user hypotheses in problem diagnosis on the web and elsewhere. In Proceedings of the International Conference on Intelligent User Interfaces. 30-37.
47. WONG, W.-K., OBERST, I., DAS, S., MOORE, T., STUMPF, S., MCINTOSH, K., AND BURNETT, M. 2011. End-user feature labeling: A locally-weighted regression approach.In Proceedings of the International Conference on Intelligent User Interfaces. 115-124.