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Semantic Integration in Heterogeneous Databases Using Neural Networks

Summary: Neural-network based semantic matching for heterogeneous DB integration: a classifier labels attributes by field specs and values, then a neural model learns to map equivalents. Discovery from metadata, not pre-programmed rules, yields the correspondences. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
8176
Venue
VLDB
Year
1994
Pagerank
6.8959519e-05
Overall Rank
3,637 | 74.70%
DOI
-

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

Rank Cited Paper Year Venue Pagerank
165 Federated Database Systems for Managing Distributed, Heterogeneous, and Autonomous Databases 1991 VLDB 0.00039502525
677 Constructing Superviews 1981 SIGMOD 0.0001826131
1,321 Intelligent Integration of Information 1993 SIGMOD 0.0001261238
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