USHER: Improving data quality with dynamic forms

Proceedings - International Conference on Data Engineering

Volumn , Issue , 2010, Pages 321-332

  Chen, Kuang ^a   Chen, Harr ^b   Conway, Neil ^a   Hellerstein, Joseph M ^a   Parikh, Tapan S ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATIC METHOD; CRITICAL PROBLEMS; CURRENT PRACTICES; DATA ENTRIES; DATA QUALITY; DATA VALUES; END-TO-END SYSTEMS; FORM DESIGN; FORM LAYOUT; LITTLE RESEARCH; PROBABILISTIC MODELS; REAL WORLD DATA; REAL-TIME FEEDBACK; REDUCED COST; THREE COMPONENT;

COST REDUCTION; QUALITY ASSURANCE; TOTAL QUALITY MANAGEMENT;

DATA REDUCTION;

EID: 77952784256     PISSN: 10844627     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDE.2010.5447832     Document Type: Conference Paper

References (29)

1. T. Dasu and T. Johnson, Exploratory Data Mining and Data Cleaning. Wiley Series in Probability and Statistics, 2003.
2. C. Batini and M. Scannapieco, Data Quality: Concepts, Methodologies and Techniques. Springer, 2006.
3. R. M. Graves, F. J. Fowler, M. P. Couper, J. M. Lepkowski, E. Singer, and R. Tourangeau, Survey Methodology. Wiley-Interscience, 2004.
4. J. Lee. (2003) Address to WHO staff. [Online]. Available: http://www.who.int/dg/lee/speeches/2003/21 07/en
5. J. V. D. Broeck, M. Mackay, N. Mpontshane, A. K. K. Luabeya, M. Chhagan, and M. L. Bennish, "Maintaining data integrity in a rural clinical trial," Controlled Clinical Trials, 2007.
6. R. McCarthy and T. Piazza, "Personal interview," University of California at Berkeley Survey Research Center, 2009.
7. S. Patnaik, E. Brunskill, and W. Thies, "Evaluating the accuracy of data collection on mobile phones: A study of forms, sms, and voice," in ICTD, 2009.
8. J. M. Hellerstein, "Quantitative data cleaning for large databases," United Nations Economic Commission for Europe (UNECE), 2008.
9. A. Ali and C. Meek, "Predictive models of form filling," Microsoft Research, Tech. Rep. MSR-TR-2009-2011, Jan. 2009.
10. L. A. Hermens and J. C. Schlimmer, "A machine-learning apprentice for the completion of repetitive forms," IEEE Expert: Intelligent Systems and Their Applications, vol. 9, no. 1, 1994.
11. D. Lee and C. Tsatsoulis, "Intelligent data entry assistant for xml using ensemble learning," in In proc. ACM IUI, 2005.
12. J. C. Schlimmer and P. C. Wells, "Quantitative results comparing three intelligent interfaces for information capture," Journal of Artificial Intelligence Research, vol. 5, 1996.
13. S. S. J.R. Warren, A. Davidovic and P. Bolton, "Mediface: anticipative data entry interface for general practitioners," in In proc. of OzCHI, 1998.
14. J. Warren and P. Bolton, "Intelligent split menus for data entry: a simulation study in general practice medicine," J Amer Med Inform Assoc, 1999.
15. Y. Yu, J. A. Stamberger, A. Manoharan, and A. Paepcke, "Ecopod: a mobile tool for community based biodiversity collection building," in JCDL, 2006.
16. S. Day, P. Fayers, and D. Harvey, "Double data entry: what value, what price?" Controlled Clinical Trials, 1998.
17. D. W. King and R. Lashley, "A quantifiable alternative to double data entry," Controlled Clinical Trials, 2000.
18. K. Kleinman, "Adaptive double data entry: a probabilistic tool for choosing which forms to reenter," Controlled Clinical Trials, 2001.
19. K. L. Norman. Online survey design guide. [Online]. Available: http://lap.umd.edu/survey-design
20. A. Hartemink. Banjo: Bayesian network inference with java objects. [Online]. Available: http://www.cs.duke.edu/~amink/software/banjo
21. F. G. Cozman. JavaBayes - Bayesian Networks in Java. [Online]. Available: http://www.cs.cmu.edu/~javabayes
22. M. R. Cambridge. Infer.NET. [Online]. Available: http://research. microsoft.com/en-us/um/cambridge/projects/infernet
23. D. Heckerman, D. Geiger, and D. M. Chickering, "Learning bayesian networks: The combination of knowledge and statistical data," Machine Learning, vol. 20, no. 3, pp. 197-243, 1995.
24. F. Jelinek and R. L. Mercer, "Interpolated estimation of markov source parameters from sparse data," in Proceedings of the Workshop on Pattern Recognition in Practice, 1980.
25. C. M. Bishop, Pattern Recognition and Machine Learning. Springer, 2007.
26. J. M. Bernardo and A. F. Smith, Bayesian Theory. Wiley Series in Probability and Statistics, 2000.
27. T. P. Minka, "Expectation propagation for approximate bayesian inference," in Proceedings of the Conference in Uncertainty in Artificial Intelligence, 2001.
28. U. C. Berkeley. Survey documentation and analysis. [Online]. Available: http://sda.berkeley.edu
29. The millennium villages project. [Online]. Available: http://www.millenniumvillages.org