DBScholar

Back to papers

Semantic Integration in Heterogeneous Databases Using Neural Networks

Summary: Learns semantic correspondences between attributes in heterogeneous databases from field specifications, data values, and metadata. A classifier and neural network discover matching rules from examples rather than relying on hand-coded schema-matching heuristics. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
h7fa84b48a4414d6f
Venue
VLDB
Year
1994
Pagerank
7.093474e-05
Overall Rank
3,692 | 75.18%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{li_vldb94,
        title = {{Semantic Integration in Heterogeneous Databases Using Neural Networks}},
        author = {Li, Wen-Syan and Clifton, Chris},
        journal = {PVLDB},
        series = {{VLDB} '94},
        year = {1994}
}

Incoming Citations (Sorted by Pagerank)

Showing 6 of 6 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

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

Rank Cited Paper Year Venue Pagerank
186 Federated Database Systems for Managing Distributed, Heterogeneous, and Autonomous Databases 1991 VLDB 0.00025951043
1,073 Constructing Superviews 1981 SIGMOD 0.00012163751
1,611 Intelligent Integration of Information 1993 SIGMOD 0.00010073084
Previous Page 1 / 1 Next

Semantically Similar Papers