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Indexing and Selecting Hierarchical Business Logic

Summary: Tree-based hierarchical indexes model semantic hierarchies for business rules, with memory-efficient variants. Uses a priority score, conflict-free ranking and a weight-based lazy merge for fast top-rule selection; evaluated on real and synthetic data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11232
Venue
VLDB
Year
2015
Pagerank
5.5313703e-05
Overall Rank
7,852 | 46.13%
DOI
10.14778/2824032.2824064

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{loro_vldb15,
        title = {{Indexing and Selecting Hierarchical Business Logic}},
        author = {Loro, Alessandra and Gruenheid, Anja and Kossmann, Donald and Profeta, Damien and Beaudequin, Philippe},
        journal = {PVLDB},
        series = {{VLDB} '15},
        volume = {8},
        number = {12},
        pages = {1656--1669},
        doi = {10.14778/2824032.2824064},
        url = {https://doi.org/10.14778/2824032.2824064},
        year = {2015}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
9,568 Making Search Engines Faster by Lowering the Cost of Querying Business Rules Through FPGAs 2020 SIGMOD 5.2528121e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

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

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