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LM-SRPQ: Efficiently Answering Regular Path Query in Streaming Graphs

Summary: LM-SRPQ: hybrid persistent-RPQ for streaming graphs combining selective materialization of intermediate results with real-time traversal. Merges redundant storage and computation to cut memory and time; extensive experiments show clear gains over prior art. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13542
Venue
VLDB
Year
2024
Pagerank
5.5007031e-05
Overall Rank
8,046 | 44.80%
DOI
10.14778/3641204.3641214

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{gou_vldb24,
        title = {{LM-SRPQ: Efficiently Answering Regular Path Query in Streaming Graphs}},
        author = {Gou, Xiangyang and Ye, Xinyi and Zou, Lei and Yu, Jeffrey Xu},
        journal = {PVLDB},
        series = {{VLDB} '24},
        volume = {17},
        number = {5},
        pages = {1047--1059},
        doi = {10.14778/3641204.3641214},
        url = {https://doi.org/10.14778/3641204.3641214},
        year = {2024}
}

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