Nagpal, C., Miller, K., Boecking, B., & Dubrawski, A. (2017). An Entity Resolution approach to isolate instances of Human Trafficking online. Paper presented at the 3rd Workshop on Noisy User-generated Text (W-NUT) at EMNLP 2017, Copenhagen.
Boecking, B., Hall, M., & Schneider, J. (2015). Event prediction with learning algorithms—A study of events surrounding the egyptian revolution of 2011 on the basis of micro blog data. Policy & Internet, 7(2), 159-184.
Dubrawski, A., Miller, K., Barnes, M., Boecking, B., & Kennedy, E. (2015). Leveraging publicly available data to discern patterns of human-trafficking activity. Journal of Human Trafficking, 1(1), 65-85.
Boecking, B., Hall, M., & Schneider, J. (2014). Predicting Events Surrounding the Egyptian Revolution of 2011 Using Learning Algorithms on Micro Blog Data. Paper presented at Internet, Politics, and Policy 2014: Crowdsourcing for Politics and Policy, University of Oxford (2014). Best Paper Award
Boecking, B., Chalup, S. K., Seese, D., & Wong, A. S. (2014). Support vector clustering of time series data with alignment kernels. Pattern Recognition Letters, 45, 129-135.