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Ontology-based Entity Matching in Attributed Graphs

Summary: Proposes Ontological Graph Keys (OGKs): ontology-guided matching extends graph keys to semantically align label-diff entities. Shows NP-complete for implication/validation; offers minimal-cover and budgeted Chase-based matching on real graphs. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11818
Venue
VLDB
Year
2019
Pagerank
4.516252e-05
Overall Rank
8,405 | 41.59%
DOI
10.14778/3339490.3339501

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
4,837 Entity Resolution with Hierarchical Graph Attention Networks 2022 SIGMOD 5.8835638e-05
6,086 Subgraph Matching over Graph Federation 2022 VLDB 5.2157921e-05
11,459 Temporal Dependencies for Graphs 2021 SIGMOD 4.1905499e-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.

Rank Cited Paper Year Venue Pagerank
1,820 A Normal Form for XML Documents 2002 PODS 0.00010410152
2,422 From Data Fusion to Knowledge Fusion 2014 VLDB 8.8452901e-05
2,517 Dependencies for Graphs 2017 PODS 8.6058545e-05
2,728 Keys for Graphs 2015 VLDB 8.2228869e-05
3,177 Evaluating Entity Resolution Results 2010 VLDB 7.4367336e-05
3,478 Functional Dependencies for Graphs 2016 SIGMOD 7.0554625e-05
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