most citedPrivacy-Preserving Multiple Tensor Factorization for Synthesizing Large-Scale Location Traces with Cluster-Specific Features

2 citations · 2 across the 1 of their papers we have counts for

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1 paper

cs.CR2019★ 2 cited

Privacy-Preserving Multiple Tensor Factorization for Synthesizing Large-Scale Location Traces with Cluster-Specific Features

Takao Murakami, Koki Hamada, Yusuke Kawamoto +1

With the widespread use of LBSs (Location-based Services), synthesizing location traces plays an increasingly important role in analyzing spatial big data while protecting user pri…