Greedy algorithms for the profit-aware social team formation problem

Shengxin Liu () and Chung Keung Poon ()
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Shengxin Liu: Harbin Institute of Technology (Shenzhen)
Chung Keung Poon: The Hang Seng University of Hong Kong

Journal of Combinatorial Optimization, 2022, vol. 44, issue 1, No 5, 94-118

Abstract: Abstract Motivated by applications in online labor markets, we study the problem of forming multiple teams of experts in a social network to accomplish multiple tasks that require different combinations of skills. Our goal is to maximize the total profit of tasks that are completed by these teams subject to the capacity constraints of the experts. We study both the offline and online settings of the problem. For the offline problem, we present a simple and practical algorithm that improves upon previous results in many situations. For the online problem, we design competitive deterministic and randomized online algorithms. These are complemented by some hardness results in both settings.

Keywords: Team formation; Greedy algorithms; Social networks; Lower bounds (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10878-021-00817-y

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