Enhancing crowdsourcing through skill and willingness-aligned task assignment with workforce composition balance

IF 3 3区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Pervasive and Mobile Computing Pub Date : 2025-02-01 DOI:10.1016/j.pmcj.2025.102012

Riya Samanta , Soumya K. Ghosh , Sajal K. Das

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引用次数: 0

Abstract

Crowdsourcing platforms face critical challenges in task assignment and workforce retention, particularly in aligning complex, skill-intensive tasks with crowd-worker willingness and potential while ensuring workforce diversity and balanced composition. This study introduces the Skill-Aligned Task Assignment and Potential-Aware Workforce Composition (SATA-PAW) framework to address these challenges. The proposed framework formulates the Task Assignment with Workforce Composition Balance (TACOMB) problem as a multi-constraint optimization task, aiming to maximize net utility under task budget constraints while promoting balanced workforce composition. SATA-PAW integrates two novel algorithms, Skill-Aligned Task Assignment (SATA), which optimizes task-worker matching by considering skills, willingness, and budget constraints, and Potential-Aware Workforce Composition (PAW), which leverages satisfaction score and latent potential to retain skilled workers and improve workforce diversity. Experimental evaluations on real-world (UpWork) and synthetic datasets demonstrate SATA-PAW’s superiority over five state-of-the-art methods. The results highlight SATA-PAW’s ability to integrate human-centric factors with efficient optimization, setting a new benchmark for skill-oriented task assignment and balanced workforce composition in crowdsourcing systems.

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来源期刊

Pervasive and Mobile Computing COMPUTER SCIENCE, INFORMATION SYSTEMS-TELECOMMUNICATIONS

CiteScore

7.70

自引率

2.30%

发文量

审稿时长

68 days

期刊介绍： As envisioned by Mark Weiser as early as 1991, pervasive computing systems and services have truly become integral parts of our daily lives. Tremendous developments in a multitude of technologies ranging from personalized and embedded smart devices (e.g., smartphones, sensors, wearables, IoTs, etc.) to ubiquitous connectivity, via a variety of wireless mobile communications and cognitive networking infrastructures, to advanced computing techniques (including edge, fog and cloud) and user-friendly middleware services and platforms have significantly contributed to the unprecedented advances in pervasive and mobile computing. Cutting-edge applications and paradigms have evolved, such as cyber-physical systems and smart environments (e.g., smart city, smart energy, smart transportation, smart healthcare, etc.) that also involve human in the loop through social interactions and participatory and/or mobile crowd sensing, for example. The goal of pervasive computing systems is to improve human experience and quality of life, without explicit awareness of the underlying communications and computing technologies. The Pervasive and Mobile Computing Journal (PMC) is a high-impact, peer-reviewed technical journal that publishes high-quality scientific articles spanning theory and practice, and covering all aspects of pervasive and mobile computing and systems.