2024

Selecting workers like expert for crowdsourcing by integration evaluation of individual and collaborative abilities
Selecting workers like expert for crowdsourcing by integration evaluation of individual and collaborative abilities

Yaohui Han, Mingyang Zhao, Nuanqiao Shan, Anfeng Liu, Tian Wang, Houbing Song, Shaobo Zhang

Expert Systems With Applications (ESWA) 2024 Journal

We propose an Integration of Individual and Collaborative Abilities based Dynamic Worker Selection (IICA-DWS) algorithm to recruit excellent workers as a team in a high-quality and low-cost style. In the IICA-DWS algorithm, each worker’s individual ability and collaborative contribution to the team are evaluated more accurately using the Approximate Shapley Value (ASV). In addition, a high-quality team formation method is established to complete complex tasks at low cost. This involves the selection of both team leaders and team members. In this process, the Multi-Armed Bandit (MAB) model is adopted to dynamically select excellent workers using exploration and exploitation phases. Lastly, the IICA-DWS algorithm is evaluated through theoretical analysis and experimental results.

[Code] [Paper]

Selecting workers like expert for crowdsourcing by integration evaluation of individual and collaborative abilities
Selecting workers like expert for crowdsourcing by integration evaluation of individual and collaborative abilities

Yaohui Han, Mingyang Zhao, Nuanqiao Shan, Anfeng Liu, Tian Wang, Houbing Song, Shaobo Zhang

Expert Systems With Applications (ESWA) 2024 Journal

We propose an Integration of Individual and Collaborative Abilities based Dynamic Worker Selection (IICA-DWS) algorithm to recruit excellent workers as a team in a high-quality and low-cost style. In the IICA-DWS algorithm, each worker’s individual ability and collaborative contribution to the team are evaluated more accurately using the Approximate Shapley Value (ASV). In addition, a high-quality team formation method is established to complete complex tasks at low cost. This involves the selection of both team leaders and team members. In this process, the Multi-Armed Bandit (MAB) model is adopted to dynamically select excellent workers using exploration and exploitation phases. Lastly, the IICA-DWS algorithm is evaluated through theoretical analysis and experimental results.

[Code] [Paper]