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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
8177
Venue
VLDB
Year
1994
Pagerank
6.8893259e-05
Overall Rank
3,638 | 74.72%
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
166 Federated Database Systems for Managing Distributed, Heterogeneous, and Autonomous Databases 1991 VLDB 0.00039467886
678 Constructing Superviews 1981 SIGMOD 0.0001824315
1,319 Intelligent Integration of Information 1993 SIGMOD 0.00012608305
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