Team expansion in collaborative environments

Lun Zhao; Yuan Yao; Guibing Guo; Hanghang Tong; Feng Xu; Jian Lu

doi:10.1007/978-3-319-93040-4_56

Team expansion in collaborative environments

Lun Zhao, Yuan Yao, Guibing Guo, Hanghang Tong, Feng Xu, Jian Lu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

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.

Original language	English (US)
Title of host publication	Advances in Knowledge Discovery and Data Mining - 22nd Pacific-Asia Conference, PAKDD 2018, Proceedings
Editors	Geoffrey I. Webb, Dinh Phung, Mohadeseh Ganji, Lida Rashidi, Vincent S. Tseng, Bao Ho
Publisher	Springer Verlag
Pages	713-725
Number of pages	13
ISBN (Print)	9783319930398
DOIs	https://doi.org/10.1007/978-3-319-93040-4_56
State	Published - 2018
Event	22nd Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2018 - Melbourne, Australia Duration: Jun 3 2018 → Jun 6 2018

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10939 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	22nd Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2018
Country/Territory	Australia
City	Melbourne
Period	6/3/18 → 6/6/18

Keywords

Candidate member prediction
Collaborative environments
Neural networks
Team expansion

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-319-93040-4_56

Cite this

Zhao, L., Yao, Y., Guo, G., Tong, H., Xu, F., & Lu, J. (2018). Team expansion in collaborative environments. In G. I. Webb, D. Phung, M. Ganji, L. Rashidi, V. S. Tseng, & B. Ho (Eds.), Advances in Knowledge Discovery and Data Mining - 22nd Pacific-Asia Conference, PAKDD 2018, Proceedings (pp. 713-725). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10939 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-319-93040-4_56

Team expansion in collaborative environments. / Zhao, Lun; Yao, Yuan; Guo, Guibing et al.
Advances in Knowledge Discovery and Data Mining - 22nd Pacific-Asia Conference, PAKDD 2018, Proceedings. ed. / Geoffrey I. Webb; Dinh Phung; Mohadeseh Ganji; Lida Rashidi; Vincent S. Tseng; Bao Ho. Springer Verlag, 2018. p. 713-725 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10939 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Zhao, L, Yao, Y, Guo, G, Tong, H, Xu, F & Lu, J 2018, Team expansion in collaborative environments. in GI Webb, D Phung, M Ganji, L Rashidi, VS Tseng & B Ho (eds), Advances in Knowledge Discovery and Data Mining - 22nd Pacific-Asia Conference, PAKDD 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10939 LNAI, Springer Verlag, pp. 713-725, 22nd Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2018, Melbourne, Australia, 6/3/18. https://doi.org/10.1007/978-3-319-93040-4_56

Zhao L, Yao Y, Guo G, Tong H, Xu F, Lu J. Team expansion in collaborative environments. In Webb GI, Phung D, Ganji M, Rashidi L, Tseng VS, Ho B, editors, Advances in Knowledge Discovery and Data Mining - 22nd Pacific-Asia Conference, PAKDD 2018, Proceedings. Springer Verlag. 2018. p. 713-725. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-93040-4_56

Zhao, Lun ; Yao, Yuan ; Guo, Guibing et al. / Team expansion in collaborative environments. Advances in Knowledge Discovery and Data Mining - 22nd Pacific-Asia Conference, PAKDD 2018, Proceedings. editor / Geoffrey I. Webb ; Dinh Phung ; Mohadeseh Ganji ; Lida Rashidi ; Vincent S. Tseng ; Bao Ho. Springer Verlag, 2018. pp. 713-725 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "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.",

keywords = "Candidate member prediction, Collaborative environments, Neural networks, Team expansion",

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note = "Funding Information: 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. Funding Information: 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. Publisher Copyright: {\textcopyright} Springer International Publishing AG, part of Springer Nature 2018.; 22nd Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2018 ; Conference date: 03-06-2018 Through 06-06-2018",

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N1 - Funding Information: 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. Funding Information: 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. Publisher Copyright: © Springer International Publishing AG, part of Springer Nature 2018.

PY - 2018

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ER -

Team expansion in collaborative environments

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Keywords

ASJC Scopus subject areas

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