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Efficient Recovery of Missing Events

Summary: Efficient recovery of missing events from logs via a branching framework compactly representing feasible sequences under a min-change objective. Indexing and pruning yield top-k recoveries, up to 5 orders of magnitude faster than prior work. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10933
Venue
VLDB
Year
2013
Pagerank
5.5077375e-05
Overall Rank
8,008 | 45.06%
DOI
10.14778/2536206.2536212

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{wang_vldb13,
        title = {{Efficient Recovery of Missing Events}},
        author = {Wang, Jianmin and Song, Shaoxu and Zhu, Xiaochen and Lin, Xuemin},
        journal = {PVLDB},
        series = {{VLDB} '13},
        volume = {6},
        number = {10},
        pages = {841--852},
        doi = {10.14778/2536206.2536212},
        url = {https://doi.org/10.14778/2536206.2536212},
        year = {2013}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
3,386 Efficient and Effective Data Imputation with Influence Functions 2022 VLDB 7.453827e-05
5,519 Repairing Vertex Labels under Neighborhood Constraints 2014 VLDB 6.1885644e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 8 of 8 cited papers.

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

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