Bibliography

Found 44 results
Title [ Type(Desc)] Year
Filters: Term is Data Mining  [Clear All Filters]
Conference Paper
Shmueli, G., and O. Koppius, "Predictive vs. Explanatory Modeling in IS Research", Conference on Information Systems & Technology (Best Paper Award), Seattle, WA, 03/11/2007.
Gupta, R., D. Mani, S. Mithas, and G. Shmueli, "Tree Matching Solution for Self-Selection in Impact Surveys", Statistical Challenges in Ecommerce Research (SCECR), Montreal, Canada, 28/06/2012. PDF icon SCECR 2012 Poster Tree Matching for Self-Selection in Impact Surveys.pdf (807.52 KB)
Conference Proceedings
Lotze, T., and G. Shmueli, "Ensemble Forecasting for Disease Outbreak Detection", 23rd AAAI Conference on Artificial Intelligence (AAAI-08), Chicago, IL, 2008. PDF icon AAAI7LotzeT.pdf (61 KB)
Yahav, I., and G. Shmueli, "Predicting Potential Survival Rates of Kidney Transplant Candidates From Databases With Existing Allocation Policies", 5th INFORMS Workshop on Data Mining and Healh Informatics, Austin, TX, 05/11/2010. PDF icon INFORMS 2010 DMHI.pdf (123.33 KB)
Shmueli, G., and C. Soares, "Teaching Data Mining in the Business School: Experience from Three Continents", Teaching Machine Learning Workshop, ICML, Edinburgh, Scotland, UK, June 2012. PDF icon ICML 2012 Teaching BS vs CS.pdf (413.83 KB)
Shmueli, G., and O. Koppius, "What is Predictive about Partial Least Squares?", Sixth Symposium on Statistical Challenges in eCommerce Research (SCECR), University of Texas at Austin, McCombs School of Business, TX, 05/06/2010. PDF icon Conference Paper (285.09 KB)
Journal Article
"Accelerating Statistical Research in Drug Safety", Pharmacoepidemiology and Drug Safety, vol. 15, issue 9, pp. 687-688, 2006.
Greene, T., G. Shmueli, S. Ray, and J. Fell, "Adjusting to the GDPR: The Impact on Data Scientists and Behavioral Researchers", Big data, 2019.
Ashouri, M., K. Cai, FR. Lin, and G. Shmueli, "Assessing the Value of an Information System for Developing Predictive Analytics: The Case of Forecasting School-Level Demand in Taiwan", Service Science, vol. 10, pp. 58–75, 2018.
Shmueli, G., and O. Koppius, "The Challenge of Prediction in Information Systems Research", Working Paper (RHS 06-058) : Smith School of Business, University of Maryland, 2009.
Shmueli, G., and I. Yahav, "The Forest or the Trees? Tackling Simpson's Paradox with Classification Trees", Production and Operations Management, vol. 27, pp. 696–716, 2018.
Kenett, R. S., and G. Shmueli, "On Information Quality", JRSS A, vol. 177, issue 1, pp. 3-27, 2014. PDF icon Kenett Shumeli JRSSA 2014.pdf (689.6 KB)
Dass, M., W. Jank, and G. Shmueli, "Maximizing Bidder Surplus in Simultaneous Online Art Auctions via Dynamic Forecasting", International Journal on Forecasting, vol. 27, issue 4, pp. 1259-1270, 2011.
Yahav, I., and G. Shmueli, "Outcomes matter: estimating pre-transplant survival rates of kidney-transplant patients using simulator-based propensity scores", Annals of Operations Research, vol. 216, issue 1, pp. 101-128, 2014. PDF icon lifetime_r2.pdf (924.59 KB)
Shmueli, G., and O. Koppius, "Predictive Analytics in Information Systems Research", MIS Quarterly, vol. 35, issue 3, pp. 553-572, 2011. PDF icon MISQ-Predictive-Analytics-in-IS-Shmueli-Koppius -2011.pdf (303.74 KB)
Zhang, S., W. Jank, and G. Shmueli, "Real-Time Forecasting of Online Auctions via Functional K-Nearest Neighbors", International Journal of Forecasting, vol. 26, pp. 666-683, 2010. PDF icon IJF 2010 Realtime forecasting auctions fKNN.pdf (478.32 KB)
Shmueli, G., "To Explain or To Predict?", Working Paper (RHS 06-099) Smith School of Business, University of Maryland, 2009.
Shmueli, G., "To Explain or To Predict?", Statistical Science, vol. 25, issue 3, pp. 289-310, 2010. PDF icon Stat Science published.pdf (293.36 KB)
Yahav, I., G. Shmueli, and D. Mani, "A Tree-Based Approach for Addressing Self-Selection in Impact Studies with Big Data", MIS Quarterly, vol. 40, issue 4, pp. 819-848, 2016.
Yahav, I., G. Shmueli, and D. Mani, "A Tree-Based Approach for Addressing Self-Selection in Impact Studies with Big Data", MIS Quarterly, vol. 40, issue 4, pp. 819-848, 2016.

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