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LOCATER: Cleaning WiFi Connectivity Datasets for Semantic Localization

Summary: LOCATER reframes semantic indoor localization as data cleaning: fix missing AP-device links across WiFi events and map devices to semantic subregions. Bootstrapped semi-supervised learning yields coarse localization, while probabilistic refinement achieves fine-grained, room-like accuracy. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12728
Venue
VLDB
Year
2021
Pagerank
5.093636e-05
Overall Rank
11,733 | 19.51%
DOI
10.14778/3430915.3430923

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Authors

BibTeX Citation

@article{lin_vldb21,
        title = {{LOCATER: Cleaning WiFi Connectivity Datasets for Semantic Localization}},
        author = {Lin, Yiming and Jiang, Daokun and Yus, Roberto and Bouloukakis, Georgios and Chio, Andrew and Mehrotra, Sharad and Venkatasubramanian, Nalini},
        journal = {PVLDB},
        series = {{VLDB} '21},
        volume = {14},
        number = {3},
        pages = {329--341},
        doi = {10.14778/3430915.3430923},
        url = {https://doi.org/10.14778/3430915.3430923},
        year = {2021}
}

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