A Recommendation Method for Social Collaboration Tasks Based on Personal Social Preferences

Wang, Jiaqiu; Wang, Zhongjie; Li, Jin

doi:10.1109/access.2018.2863543

Cited by 2 publications

(1 citation statement)

References 21 publications

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“…Some scholars have provided task lists by analyzing the social attributes of workers and referring to the task choices of similar workers. Wang et al [30] proposed a universal recommendation method based on personal socialcollaboration preferences, which was used to recommend the social-collaboration tasks that individuals can participate in. Li et al [31] obtained behavioral information of users from social networks as well as crowdsourcing platforms.…”

Section: Related Workmentioning

confidence: 99%

A Task Recommendation Model in Mobile Crowdsourcing

Qiu

et al. 2022

Wireless Communications and Mobile Computing

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With the development of the Internet of Things and the popularity of smart terminal devices, mobile crowdsourcing systems are receiving more and more attention. However, the information overload of crowdsourcing platforms makes workers face difficulties in task selection. This paper proposes a task recommendation model based on the prediction of workers’ mobile trajectories. A recurrent neural network is used to obtain the movement pattern of workers and predict the next destination. In addition, an attention mechanism is added to the task recommendation model in order to capture records that are similar to candidate tasks and to obtain task selection preferences. Finally, we conduct experiments on two real datasets, Foursquare and AMT (Amazon Mechanical Turk), to verify the effectiveness of the proposed recommendation model.

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Section: Related Workmentioning

confidence: 99%