TY - GEN
T1 - Team expansion in collaborative environments
AU - Zhao, Lun
AU - Yao, Yuan
AU - Guo, Guibing
AU - Tong, Hanghang
AU - Xu, Feng
AU - Lu, Jian
N1 - This work is supported by the National Natural Science Foundation of China (No. 61690204, 61672274, 61702252), the National Key Research and Development Program of China (No. 2016YFB1000802), the Fundamental Research Funds for the Central Universities (No. 020214380033), and the Collaborative Innovation Center of Novel Software Technology and Industrialization. Guibing Guo is partially supported by the National Natural Science Foundation for Young Scientists of China (No. 61702084). Hanghang Tong is partially supported by NSF (IIS-1651203, IIS-1715385, CNS-1629888 and IIS-1743040), DTRA (HDTRA1-16-0017), ARO (W911NF-16-1-0168), and gifts from Huawei and Baidu.
Acknowledgments. This work is supported by the National Natural Science Foundation of China (No. 61690204, 61672274, 61702252), the National Key Research and Development Program of China (No. 2016YFB1000802), the Fundamental Research Funds for the Central Universities (No. 020214380033), and the Collaborative Innovation Center of Novel Software Technology and Industrialization. Guibing Guo is partially supported by the National Natural Science Foundation for Young Scientists of China (No. 61702084). Hanghang Tong is partially supported by NSF (IIS-1651203, IIS-1715385, CNS-1629888 and IIS-1743040), DTRA (HDTRA1-16-0017), ARO (W911NF-16-1-0168), and gifts from Huawei and Baidu.
PY - 2018
Y1 - 2018
N2 - In this paper, we study the team expansion problem in collaborative environments where people collaborate with each other in the form of a team, which might need to be expanded frequently by having additional team members during the course of the project. Intuitively, there are three factors as well as the interactions between them that have a profound impact on the performance of the expanded team, including (1) the task the team is performing, (2) the existing team members, and (3) the new candidate team member. However, the vast majority of the existing work either considers these factors separately, or even ignores some of these factors. In this paper, we propose a neural network based approach TECE to simultaneously model the interactions between the team task, the team members as well as the candidate team members. Experimental evaluations on real-world datasets demonstrate the effectiveness of the proposed approach.
AB - In this paper, we study the team expansion problem in collaborative environments where people collaborate with each other in the form of a team, which might need to be expanded frequently by having additional team members during the course of the project. Intuitively, there are three factors as well as the interactions between them that have a profound impact on the performance of the expanded team, including (1) the task the team is performing, (2) the existing team members, and (3) the new candidate team member. However, the vast majority of the existing work either considers these factors separately, or even ignores some of these factors. In this paper, we propose a neural network based approach TECE to simultaneously model the interactions between the team task, the team members as well as the candidate team members. Experimental evaluations on real-world datasets demonstrate the effectiveness of the proposed approach.
KW - Candidate member prediction
KW - Collaborative environments
KW - Neural networks
KW - Team expansion
UR - https://www.scopus.com/pages/publications/85049366608
UR - https://www.scopus.com/pages/publications/85049366608#tab=citedBy
U2 - 10.1007/978-3-319-93040-4_56
DO - 10.1007/978-3-319-93040-4_56
M3 - Conference contribution
AN - SCOPUS:85049366608
SN - 9783319930398
T3 - Lecture Notes in Computer Science
SP - 713
EP - 725
BT - Advances in Knowledge Discovery and Data Mining - 22nd Pacific-Asia Conference, PAKDD 2018, Proceedings
A2 - Phung, Dinh
A2 - Tseng, Vincent S.
A2 - Webb, Geoffrey I.
A2 - Ho, Bao
A2 - Ganji, Mohadeseh
A2 - Rashidi, Lida
PB - Springer
T2 - 22nd Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2018
Y2 - 3 June 2018 through 6 June 2018
ER -