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With the widespread diffusion of smartphones, Spatial Crowdsourcing (SC), which aims to assign spatial tasks to mobile workers, has drawn increasing attention in both academia and industry. One of the major issues is how to best assign…
Spatial crowdsourcing (SC) engages large worker pools for location-based tasks, attracting growing research interest. However, prior SC task allocation approaches exhibit limitations in computational efficiency, balanced matching, and…
Recently, with the rapid development of mobile devices and the crowdsourcing platforms, the spatial crowdsourcing has attracted much attention from the database community. Specifically, spatial crowdsourcing refers to sending a…
With the rapid development of mobile devices and crowdsourcing platforms, the spatial crowdsourcing has attracted much attention from the database community. Specifically, the spatial crowdsourcing refers to sending location-based requests…
Spatial Crowdsourcing (SC) is a novel platform that engages individuals in the act of collecting various types of spatial data. This method of data collection can significantly reduce cost and turnover time, and is particularly useful in…
Spatial crowdsourcing refers to a system that periodically assigns a number of location-based workers with spatial tasks nearby (e.g., taking photos or videos at some spatial locations). Previous works on the spatial crowdsourcing usually…
Spatial Crowdsourcing (SC) is gaining traction in both academia and industry, with tasks on SC platforms becoming increasingly complex and requiring collaboration among workers with diverse skills. Recent research works address complex…
Asynchronous methods are fundamental for parallelizing computations in distributed machine learning. They aim to accelerate training by fully utilizing all available resources. However, their greedy approach can lead to inefficiencies using…
With the rapid development of Mobile Internet, spatial crowdsourcing is gaining more and more attention from both academia and industry. In spatial crowdsourcing, spatial tasks are sent to workers based on their locations. A wide kind of…
Wireless power transfer (WPT) is a promising technology to prolong the lifetime of the sensors and communication devices, i.e., workers, in completing crowdsourcing tasks by providing continuous and cost-effective energy supplies. In this…
Mobile crowdsourcing refers to systems where the completion of tasks necessarily requires physical movement of crowdworkers in an on-demand workforce. Evidence suggests that in such systems, tasks often get assigned to crowdworkers who…
This paper addresses the data-locality-aware task assignment and scheduling problem for distributed job executions. Our goal is to minimize job completion times without prior knowledge of future job arrivals. We propose an Optimal Balanced…
Crowdsourcing systems, in which numerous tasks are electronically distributed to numerous "information piece-workers", have emerged as an effective paradigm for human-powered solving of large scale problems in domains such as image…
Spatio-temporal machine learning is critically needed for a variety of societal applications, such as agricultural monitoring, hydrological forecast, and traffic management. These applications greatly rely on regional features that…
We consider the problem of optimal budget allocation for crowdsourcing problems, allocating users to tasks to maximize our final confidence in the crowdsourced answers. Such an optimized worker assignment method allows us to boost the…
Accurate demand forecasting is critical for enhancing the efficiency and responsiveness of food delivery platforms, where spatial heterogeneity and temporal fluctuations in order volumes directly influence operational decisions. This paper…
With the rapid development of mobile devices and the crowdsourcig platforms, the spatial crowdsourcing has attracted much attention from the database community, specifically, spatial crowdsourcing refers to sending a location-based request…
Driven by the unceasing development of maritime services, tasks of unmanned aerial vehicle (UAV)-assisted maritime data collection (MDC) are becoming increasingly diverse, complex and personalized. As a result, effective task allocation for…
In this paper, we study a novel spatial crowdsourcing system where the workers' time availabilities and their spatial locations are known a priori. Consequently, the tasks assignment to workers is performed not only based on the current…
The prevalence of mobile internet techniques stimulates the emergence of various spatial crowdsourcing applications. Certain of the applications serve for requesters, budget providers, who submit a batch of tasks and a fixed budget to…