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Kamel: A Scalable BERT-based System for Trajectory Imputation

Summary: Kamel recasts trajectory imputation as masked-word prediction, adapting BERT with spatial awareness and multi-point inference. Its scalable design handles city-scale trajectories, large gaps, and tight accuracy thresholds, outperforming prior methods on real data. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
13920
Venue
VLDB
Year
2024
Pagerank
5.6029996e-05
Overall Rank
7,505 | 48.51%
DOI
10.14778/3632093.3632113

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{musleh_vldb24,
        title = {{Kamel: A Scalable BERT-based System for Trajectory Imputation}},
        author = {Musleh, Mashaal and Mokbel, Mohamed F.},
        journal = {PVLDB},
        series = {{VLDB} '24},
        volume = {17},
        number = {3},
        pages = {525--538},
        doi = {10.14778/3632093.3632113},
        url = {https://doi.org/10.14778/3632093.3632113},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
10,561 MH-GIN: Multi-scale Heterogeneous Graph-based Imputation Network for AIS Data 2026 VLDB 5.093636e-05
11,061 Large Language Models for Spatial Analysis Queries 2025 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 6 of 6 cited papers.

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

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