References
- T. D. LaToza and A. Van der Hoek, "Crowdsourcing in software engineering: models, motivations, and challenges," IEEE Software, vol. 33, no. 1, pp. 74-80, 2016. https://doi.org/10.1109/MS.2016.12
- K. Mao, L. Capra, M. Harman, and Y. Jia, "A survey of the use of crowdsourcing in software engineering," Journal of Systems and Software, vol. 126, pp. 57-84, 2017. https://doi.org/10.1016/j.jss.2016.09.015
- K. Mao, Y. Yang, Q. Wang, Y. Jia, and M. Harman, "Developer recommendation for crowdsourced software development tasks," in Proceedings of 2015 IEEE Symposium on Service-Oriented System Engineering, San Francisco Bay, CA, 2015, pp. 347-356.
- L. B. Chilton, J. J. Horton, R. C. Miller, and S. Azenkot, "Task search in a human computation market," in Proceedings of the ACM SIGKDD Workshop on Human Computation, Washington, DC, 2010, pp. 1-9.
- E. Aldhahri, V. Shandilya, and S. Shiva, "Towards an effective crowdsourcing recommendation system: a survey of the state-of-the-art," in Proceedings of 2015 IEEE Symposium on Service-Oriented System Engineering, San Francisco Bay, CA, 2015, pp. 372-377.
- T. D. LaToza and A. Van der Hoek, "A vision of crowd development," in Proceedings of 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering, Florence, Italy, 2015, pp. 563-566.
- D. Geiger and M. Schader, "Personalized task recommendation in crowdsourcing information systems: current state of the art," Decision Support Systems, vol. 65, pp. 3-16, 2014. https://doi.org/10.1016/j.dss.2014.05.007
- D. Dang, Y. Liu, X. Zhang, and S. Huang, "A crowdsourcing worker quality evaluation algorithm on MapReduce for big data applications," IEEE Transactions on Parallel and Distributed Systems, vol. 27, no. 7, pp. 1879-1888, 2016. https://doi.org/10.1109/TPDS.2015.2457924
- B. Carpenter, "Multilevel Bayesian models of categorical data annotation," 2008 [Online]. Available: https://lingpipe.files.wordpress.com/2008/11/carp-bayesian-multilevel-annotation.pdf.
- A. Brew, D. Greene, and P. Cunningham, "Using crowdsourcing and active learning to track sentiment in online media," in Proceedings of the 19th European Conference on Artificial Intelligence, Lisbon, Portugal, 2010, pp. 145-150.
- J. Howe, "The rise of crowdsourcing," Wired Magazine, vol. 14, no. 6, pp. 1-4, 2006.
- L. Machado, R. Prikladnicki, F. Meneguzzi, C. R. de Souza, and E. Carmel, "Task allocation for crowdsourcing using AI planning," in Proceedings of the 3rd International Workshop on CrowdSourcing in Software Engineering, Austin, TX, 2016, pp. 36-40.
- Y. Fu, H. Chen, and F. Song, "STWM: a solution to self-adaptive task-worker matching in software crowdsourcing," in Proceedings of the International Conference on Algorithms and Architectures for Parallel Processing, Zhangjiajie, China, 2015, pp. 383-398.
- J. E. Tomayko and O. Hazzan, Human Aspects of Software Engineering. Hingham, MA : Charles River Media, 2004.
- R. Snow, B. O'Connor, D. Jurafsky, and A. Y. Ng, "Cheap and fast: but is it good? Evaluating non-expert annotations for natural language tasks," in Proceedings of the Conference on Empirical Methods in Natural Language Processing, Honolulu, HI, 2008, pp. 254-263.
- V. Ambati, S. Vogel, and J. G. Carbonell, "Towards task recommendation in micro-task markets," Human Computation, vol. 11, pp. 1-4, 2011.
- M. C. Yuen, I. King, and K. S. Leung, "Task matching in crowdsourcing," in Proceedings of 2011 International Conference on and 4th International Conference on Cyber, Physical and Social Computing, Dalian, China, 2011, pp. 409-412.
- V. S. Sheng, F. Provost, P. G. Ipeirotis, "Get another label? Improving data quality and data mining using multiple, noisy labelers," in Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Las Vegas, NV, 2008, pp. 614-622.
- X. Liu, M. Lu, B. C. Ooi, Y. Shen, S. Wu, and M. Zhang, "CDAS: a crowdsourcing data analytics system," Proceedings of the VLDB Endowment, vol. 5, no. 10, pp. 1040-1051, 2012. https://doi.org/10.14778/2336664.2336676
- J. Whitehill, T. F. Wu, J. Bergsma, J. R. Movellan, and P. L. Ruvolo, "Whose vote should count more: optimal integration of labels from labelers of unknown expertise," Advances in Neural Information Processing Systems, vol. 22, pp. 2035-2043, 2009.
- V. C. Raykar, S. Yu, L. H. Zhao, A. Jerebko, C. Florin, G. H. Valadez, L. Bogoni, and L. Moy, "Supervised learning from multiple experts: whom to trust when everyone lies a bit," in Proceedings of the 26th Annual International Conference on Machine Learning, 2009, pp. 889-896.
- A. P. Dempster, N. M. Laird, and D. B. Rubin, "Maximum likelihood from incomplete data via the EM algorithm," Journal of the Royal Statistical Society Series B (Methodological), vol. 39, no. 1, pp. 1-38, 1977.
- A. P. Dawid and A. M. Skene, "Maximum likelihood estimation of observer error-rates using the EM algorithm," Applied Statistics, vol. 28, no. 1, pp. 20-28, 1979. https://doi.org/10.2307/2346806
- M. R. Gupta and Y. Chen, "Theory and use of the EM algorithm," Foundations and Trends in Signal Processing, vol. 4, no. 3, pp. 223-296, 2011. https://doi.org/10.1561/2000000034
- G. McLachlan and T. Krishnan, The EM Algorithm and Extensions, 2nd ed. Hoboken, NJ: John Wiley & Sons, 2007.
- L. F. Capretz and F. Ahmed, "Making sense of software development and personality types," IT Professional, vol. 12, no. 1, pp. 6-13, 2010. https://doi.org/10.1109/MITP.2010.33
- G. Kazai, J. Kamps, and N. Milic-Frayling, "Worker types and personality traits in crowdsourcing relevance labels," in Proceedings of the 20th ACM International Conference on Information and Knowledge Management, Glasgow, Scotland, 2011, pp. 1941-1944.
- C. M. Karapicak and O. Demirors, "A case study on the need to consider personality types for software team formation," in Proceedings of the International Conference on Software Process Improvement and Capability Determination, Bremen, Germany, 2013, pp. 120-129.
- L. F. Capretz, D. Varona, and A. Raza, "Influence of personality types in software tasks choices," Computers in Human Behavior, vol. 52, pp. 373-378, 2015. https://doi.org/10.1016/j.chb.2015.05.050
- S. Cruz, F. Q. da Silva, and L. F. Capretz, "Forty years of research on personality in software engineering: a mapping study," Computers in Human Behavior, vol. 46, pp. 94-113, 2015. https://doi.org/10.1016/j.chb.2014.12.008
- R. Valencia-Garcia, F. Garcia-Sanchez, D. Castellanos-Nieves, J. T. Fernandez-Breis, and A. Toval, "Exploitation of social semantic technology for software development team configuration," IET Software, vol. 4, no. 6, pp. 373-385, 2010. https://doi.org/10.1049/iet-sen.2010.0043
- N. R. Mead, "Software engineering education: how far we've come and how far we have to go," Journal of Systems and Software, vol. 82, no. 4, pp. 571-575, 2009. https://doi.org/10.1016/j.jss.2008.12.038
- A. R. Gilal, J. Jaafar, M. Omar, S. Basri, and A. Waqas, "A rule-based model for software development team composition: team leader role with personality types and gender classification," Information and Software Technology, vol. 74, pp. 105-113, 2016. https://doi.org/10.1016/j.infsof.2016.02.007
- M. Z. Tunio, H. Luo, W. Cong, Z. Fang, A. R. Gilal, A. Abro, and S. Wenhua, "Impact of personality on task selection in crowdsourcing software development: a sorting approach," IEEE Access, vol. 5, pp. 18287-18294, 2017. https://doi.org/10.1109/ACCESS.2017.2747660
- M. Z. Tunio, H. Luo, C. Wang and F. Zhao, "Crowdsourcing software development: task assignment using PDDL artificial intelligence planning," Journal of Information Processing Systems, vol. 14, no. 1, pp. 129-139, 2018. https://doi.org/10.3745/JIPS.04.0055