Abstract
| Original language | Undefined |
|---|---|
| Title of host publication | Proceedings of the Seventeenth Australasian Document Computing Symposium (ADCS 2012) |
| Place of Publication | New York |
| Publisher | Association for Computing Machinery (ACM) |
| Pages | 62-71 |
| Number of pages | 10 |
| ISBN (Print) | 978-1-4503-1411-4 |
| DOIs | |
| Publication status | Published - Dec 2012 |
Publication series
| Name | |
|---|---|
| Publisher | ACM |
Keywords
- EWI-22837
- IR-83485
- METIS-293293
Cite this
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Multi-Aspect Group Formation using Facility Location Analysis. / Neshati, Mahmood; Beigy, Hamid; Hiemstra, Djoerd.
Proceedings of the Seventeenth Australasian Document Computing Symposium (ADCS 2012). New York : Association for Computing Machinery (ACM), 2012. p. 62-71.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
TY - GEN
T1 - Multi-Aspect Group Formation using Facility Location Analysis
AU - Neshati, Mahmood
AU - Beigy, Hamid
AU - Hiemstra, Djoerd
N1 - 10.1145/2407085.2407094
PY - 2012/12
Y1 - 2012/12
N2 - In this paper, we propose an optimization framework to retrieve an optimal group of experts to perform a given multi-aspect task/project. Each task needs a diverse set of skills and the group of assigned experts should be able to collectively cover all required aspects of the task. We consider three types of multi-aspect team formation problems and propose a unified framework to solve these problems accurately and efficiently. Our proposed framework is based on Facility Location Analysis (FLA) which is a well known branch of the Operation Research (OR). Our experiments on a real dataset show significant improvement in comparison with the state-of-the art approaches for the team formation problem.
AB - In this paper, we propose an optimization framework to retrieve an optimal group of experts to perform a given multi-aspect task/project. Each task needs a diverse set of skills and the group of assigned experts should be able to collectively cover all required aspects of the task. We consider three types of multi-aspect team formation problems and propose a unified framework to solve these problems accurately and efficiently. Our proposed framework is based on Facility Location Analysis (FLA) which is a well known branch of the Operation Research (OR). Our experiments on a real dataset show significant improvement in comparison with the state-of-the art approaches for the team formation problem.
KW - EWI-22837
KW - IR-83485
KW - METIS-293293
U2 - 10.1145/2407085.2407094
DO - 10.1145/2407085.2407094
M3 - Conference contribution
SN - 978-1-4503-1411-4
SP - 62
EP - 71
BT - Proceedings of the Seventeenth Australasian Document Computing Symposium (ADCS 2012)
PB - Association for Computing Machinery (ACM)
CY - New York
ER -