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TRIPS: A System for Translating Raw Indoor Positioning Data into Visual Mobility Semantics

Summary: TRIPS translates raw indoor positioning data into mobility semantics via a configurable end-to-end pipeline. It unifies multi-source inputs, cleans data, and exports semantics with traceable intermediate data and a flexible viewer for expert inspection. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11862
Venue
VLDB
Year
2018
Pagerank
5.6029996e-05
Overall Rank
7,514 | 48.45%
DOI
10.14778/3229863.3236224

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{li_vldb18,
        title = {{TRIPS: A System for Translating Raw Indoor Positioning Data into Visual Mobility Semantics}},
        author = {Li, Huan and Lu, Hua and Shi, Feichao and Chen, Gang and Chen, Ke and Shou, Lidan},
        journal = {PVLDB},
        series = {{VLDB} '18},
        volume = {11},
        number = {12},
        pages = {1918--1921},
        doi = {10.14778/3229863.3236224},
        url = {https://doi.org/10.14778/3229863.3236224},
        year = {2018}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
11,695 Towards Crowd-aware Indoor Path Planning 2021 VLDB 5.093636e-05
11,801 IMO: A Toolbox for Simulating and Querying “Infected” Moving Objects 2020 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
5,116 STMaker–A System to Make Sense of Trajectory Data 2014 VLDB 6.358207e-05
6,218 Vita: A Versatile Toolkit for Generating Indoor Mobility Data for Real-World Buildings 2016 VLDB 5.9425753e-05
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