task assignment optimization in collaborative crowdsourcing

A number of emerging applications, such as, collaborative document editing, sentence translation, and citizen journalism require workers with complementary skills and expertise to form groups and collaborate on complex tasks. While existing research has investigated task assignment for knowledge intensive crowdsourcing, they often ignore the aspect of collaboration among workers, that is ...

Crowdsourcing usage, task assignment methods, and crowdsourcing platforms: A systematic literature review Abstract Crowdsourcing is simply the outsourcing of different tasks or work to a diverse group of individuals in an open call for the purpose of utilizing human intelligence.

The VLDB Journal. 2018. TLDR. The notion of collaboration among crowd workers is formalized and a comprehensive optimization model for task assignment in a collaborative crowdsourcing environment is proposed, and a series of efficient exact and approximation algorithms with provable theoretical guarantees are proposed. Expand.

Collaborative crowdsourcing involves a set of workers with complementary skills who form groups and collaborate to perform complex tasks, such as editing, product design, and citizen science ...

While existing research has investigated task assignment for knowledge intensive crowdsourcing, they often ignore the aspect of collaboration among workers, that is central to the success of such tasks. Research in behavioral psychology has indicated that large groups hinder successful collaboration.

We formulate the Optimized Task Assignment problem under Dynamically Changing Environment, abbreviated as DCE-OTA, and present a strategy based on a crowdsourcing knowledge graph and a reinforcement learning framework for optimizing task assignment in the context of a crowdsourcing environment that is subject to constant change.

The assignment algorithm in collaborative crowdsourcing aims to find a suitable task allocation scheme, that is, to generate a task-worker matching set, which meet the demands for workers with multiple-skills and subtasks with time dependency. We define some of the terms in this paper as follows.

Mobile crowdsourcing outsources large-scale tasks to a crowd of mobile users. To efficiently perform such tasks, many studies on tasks assignment have been conducted. However, the existing task assignment algorithms assume that each task can be completed by single worker. In reality, there are many types of tasks, including disaster recovery, which must be processed by multiple workers. To ...

optimization in collaborative crowdsourcing. The optimization goals of collaborative crowdsourcing are akin to that of its traditional micro-task based counter-parts [16, 21] - quickly maximize the quality of the com- ... In our optimization setting, each task t has a require-ment of minimum skill per domain and maximum cost bud-get, and ...

First, we formalize the notion of collaboration among crowd workers and propose a comprehensive optimization model for task assignment in a collaborative crowdsourcing environment.

A popular and broadly applicable method is task assignment that dynamically adjusts crowd workflow parameters. In this survey, we review task assignment methods that address: heterogeneous task assignment, question assignment, and plurality problems in crowdsourcing. We discuss and contrast how these methods estimate worker performance, and ...

As the most fundamental challenge in spatial crowdsourcing, task assignment has attracted extensive attention. However, there are still some vital issues left open. ... We model each worker as an actor-critic agent, and generate the final task allocation scheme (i.e., optimization policy) via the game between agents (training the MA-A2C-AM ...

Crowdsourcing has become an efficient measure to solve machine-hard problems by embracing group wisdom, in which tasks are disseminated and assigned to a group of workers in the way of open competition. The social relationships formed during this process may in turn contribute to the completion of future tasks. In this sense, it is necessary to take social factors into consideration in the ...

Unlike other crowdsourcing frameworks, collaboration is a central tenet of Crowd4U and permeates all its features. Crowd4U provides support for end-to-end deployment of collaborative tasks and enables task decomposition, worker-to-task assignment, and e ective worker collaboration during task completion. Requesters can specify collaborative ...

DOI: 10.1109/ICDM.2015.119 Corpus ID: 2258526; Task Assignment Optimization in Collaborative Crowdsourcing @article{Rahman2015TaskAO, title={Task Assignment Optimization in Collaborative Crowdsourcing}, author={Habibur Rahman and Senjuti Basu Roy and Saravanan Thirumuruganathan and Sihem Amer-Yahia and Gautam Das}, journal={2015 IEEE International Conference on Data Mining}, year={2015}, pages ...

Crowdsourcing has open not just opportunities but also options for people to work together without boundaries it is the future of collaboration. Task assignments are the main function of any crowdsourcing platform. Many recent studies focused on the workers privacy without taking into consideration the overall task matching utility score. In this paper, we adapt the batch matching method to ...

The methodology, formulating a reasonable task assignment to find the most suitable workers for a task and achieving the desired objectives, is the most fundamental challenge in spatial crowdsourcing. Many task assignment approaches have been proposed to improve the quality of crowdsourcing results and the number of task assignment and to limit ...

In summary, from either precise skill estimation or optimal task assignment point of view, existing work can-not achieve to "assign tasks to the most suitable workers". In this paper, we propose a multi-skill-based assignmen-t approach for complex macrotasks in service crowdsourc-ing, which addresses the above both challenges simultaneous-ly.

In spatio-temporal crowdsourcing platforms, task assignment or worker selection is a major issue that influences the quality of task fulfillment [11]. In [12], the authors perform task assignments considering a task set or a set of workers based on specific optimization goals while adhering to specific spatio-temporal restrictions.

The proposed study shows the effect of task assignment in crowdsourcing, such as if a task is assigned to an appropriate worker or an inappropriate worker, what will be the consequences. The study also highlights crowdsourcing usage in the field of software engineering. All the existing task assignment methods used for assigning the task to ...

We present SmartCrowd, a framework for optimizing task assignment in knowledge-intensive crowdsourcing (KI-C). SmartCrowd distinguishes itself by formulating, for the first time, the problem of worker-to-task assignment in KI-C as an optimization problem, by proposing efficient adaptive algorithms to solve it and by accounting for human factors, such as worker expertise, wage requirements, and ...

Task Publication Time Recommendation in Spatial Crowdsourcing. A novel SC framework, namely Task Assignment with Task Publication Time Recommendation, which combines different learning models to recommend the suitable publication time for each task to ensure the timely task assignment and completion while reducing the waiting time of the task ...