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- W3133634440 abstract "This paper addresses the problem of assigning heterogeneous tasks with multiple skill requirements in crowdsourcing platforms. The aim is to find mutually exclusive, a highly-productive set of workers who can successfully complete the tasks within a given deadline and budget. We propose a timeline based weighted aggregation (TWA) technique to quantify the per-skill score of a worker. The score is computed based on the worker's profile and past work experiences. Given the worker's score, we formulate the problem as one of maximizing the productivity of all the N given tasks. A two-stage approximation solution is proposed. In the first stage, we offer a greedy-based 2-approximation algorithm for a single task. In the second stage, a local ratio based algorithm is proposed to extend the solution for multiple tasks. The overall solution is shown to be 3-approximate. Finally, simulation results using real-world data are presented to highlight the efficacy of our proposed schemes." @default.
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- W3133634440 date "2021-01-01" @default.
- W3133634440 modified "2023-10-17" @default.
- W3133634440 title "A Budget and Deadline Aware Task Assignment Scheme for Crowdsourcing Environment" @default.
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- W3133634440 doi "https://doi.org/10.1109/tetc.2021.3062843" @default.
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