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Xiangjie Kong
Researcher at Zhejiang University of Technology
Publications - 161
Citations - 6003
Xiangjie Kong is an academic researcher from Zhejiang University of Technology. The author has contributed to research in topics: Computer science & The Internet. The author has an hindex of 37, co-authored 152 publications receiving 3929 citations. Previous affiliations of Xiangjie Kong include Dalian University of Technology & Zhejiang University.
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A Cooperative Partial Computation Offloading Scheme for Mobile Edge Computing Enabled Internet of Things
TL;DR: An iterative heuristic MEC resource allocation algorithm to make the offloading decision dynamically and results demonstrate that the algorithm outperforms the existing schemes in terms of execution latency and offloading efficiency.
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Vehicular Social Networks: Enabling Smart Mobility
TL;DR: An application scenario on trajectory data-analysis-based traffic anomaly detection for VSNs and several research challenges and open issues are highlighted and discussed.
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Urban traffic congestion estimation and prediction based on floating car trajectory data
TL;DR: A novel approach to estimate and predict the urban traffic congestion using floating car trajectory data efficiently using a new fuzzy comprehensive evaluation method in which the weights of multi-indexes are assigned according to the traffic flows.
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A Survey of Collaborative Filtering-Based Recommender Systems: From Traditional Methods to Hybrid Methods Based on Social Networks
TL;DR: The recent hybrid CF-based recommendation techniques fusing social networks to solve data sparsity and high dimensionality are introduced and provide a novel point of view to improve the performance of RS, thereby presenting a useful resource in the state-of-the-art research result for future researchers.
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Green and Sustainable Cloud of Things: Enabling Collaborative Edge Computing
TL;DR: A green and sustainable virtual network embedding framework for cooperative edge computing in wireless-optical broadband access networks is put forward, which leverages a reliability function to confirm the number of backup edge devices, and embed virtual networks onto the suitable edge devices in CoTs.