Ouyang, Robin WentaoKaplan, LanceToniolo, AliceSrivastava, ManiNorman, Timothy J.2016-09-272016-09-272016-10-01Ouyang, R W, Kaplan, L, Toniolo, A, Srivastava, M & Norman, T J 2016, 'Parallel and Streaming Truth Discovery in Large-Scale Quantitative Crowdsourcing', IEEE Transactions on Parallel and Distributed Systems, vol. 27, no. 10, pp. 2984-2997. https://doi.org/10.1109/TPDS.2016.25150921045-9219http://hdl.handle.net/2164/7521ACKNOWLEDGMENTS This research is based upon work supported in part by the U.S. ARL and U.K. Ministry of Defense under Agreement Number W911NF-06-3-0001, and by the NSF under award CNS-1213140. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views or represent the official policies of the NSF, the U.S. ARL, the U.S. Government, the U.K. Ministry of Defense or the U.K. Government. The U.S. and U.K. Governments are authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation hereon. This work was done when R. W. Ouyang was a postdoc at the University of California, Los Angeles, CA.14879650engCrowdsourcingtruth discoveryquantitative taskbig dataparallel algorithmstreaming algorithmQA75 Electronic computers. Computer scienceGeneral Computer ScienceQA75Journal article10.1109/TPDS.2016.25150922710