Titlebook: Database Systems for Advanced Applications; 24th International C Guoliang Li,Jun Yang,Yongxin Tong Conference proceedings 2019 Springer Nat

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Reinforced Reliable Worker Selection for Spatial Crowdsensing Networksormation about quality of workers, guaranteeing the quality of the sensing tasks remains a key challenge. In this paper, we model the quality of workers through two factors, namely bias and variance, which describe the continuous value feature of sensing tasks. After calibrating the bias, we should

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SeqST-ResNet: A Sequential Spatial Temporal ResNet for Task Prediction in Spatial Crowdsourcingoblem is to model the spatial dependency among neighboring regions and the temporal dependency at different time scales (e.g., hourly, daily, and weekly). A recent model ST-ResNet predicts traffic flow by capturing the spatial and temporal dependencies in historical data. However, the data fragments

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A Time-Series Sockpuppet Detection Method for Dynamic Social Relationshipstion to a similarity time-series analysis problem. The experiments on two real-world datasets of Sina Weibo demonstrate that our method obtains excellent detection performance, significantly outperforming previous methods.

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PU-Shapelets: Towards Pattern-Based Positive Unlabeled Classification of Time Seriesduct supervised shapelet discovery. The shapelets are then used to build a one-nearest-neighbor classifier for online classification. Extensive experiments demonstrate the effectiveness of our method.

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