Using Machine Learning to Predict Links and Improve Steiner Tree Solutions to Team Formation Problems
The team formation problem has existed for many years in various guises. One important problem in the team formation problem is to produce small teams that have a required set of skills. We propose a framework that incorporates machine learning to predict unobserved links between collaborators, alongside improved Steiner tree problems to form small teams to cover given tasks. Our framework not only considers size of the team but also how likely are team members are going to collaborate with each other. The results show that this model consistently returns smaller collaborative teams.
KeywordsTeam formation Link prediction Steiner tree
This publication has emanated from research conducted with the financial support of Science Foundation Ireland (SFI) and is co-funded under the European Regional Development Fund under Grant Number 13/RC/2077.
- 1.Hasan, M.A., Chaoji, V., Salem, S., Zaki, M.: Link prediction using supervised learning. In: SDM 2006: Workshop on Link Analysis, Counter-Terrorism and Security (2006)Google Scholar
- 6.Lappas, T., Liu, K., Terzi, E.: Finding a team of experts in social networks. In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 467–476. ACM (2009)Google Scholar
- 10.Sharma, R., McAreavey, K., Hong, J., Ghaffar, F.: Individual-level social capital in weighted and attributed social networks. In: 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 1032–1037. IEEE (2018)Google Scholar
- 11.Spadon, G., de Carvalho, A.C.P.L.F., Rodrigues-Jr, J.F., Alves, L.G.A.: Reconstructing commuters network using machine learning and urban indicators. Sci. Rep. 9(1), 1–13 (2019)Google Scholar
- 12.Tang, J., Wu, S., Sun, J., Su, H.: Cross-domain collaboration recommendation. In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1285–1293. ACM (2012)Google Scholar
- 13.Wang, X., Zhao, Z., Ng, W.: A comparative study of team formation in social networks. In: International Conference on Database Systems for Advanced Applications, pp. 389–404. Springer (2015)Google Scholar
- 15.Wu, S., Sun, J., Tang, J.: Patent partner recommendation in enterprise social networks. In: Proceedings of the Sixth ACM International Conference on Web Search and Data Mining, pp. 43–52. ACM (2013)Google Scholar
- 16.Zhang, J., Lv, Y., Yu, P.: Enterprise social link recommendation. In: Proceedings of the 24th ACM International on Conference on Information and Knowledge Management, pp. 841–850. ACM (2015)Google Scholar