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Learning Efficiently Over Heterogeneous Databases

Summary: CastorX extends relational learning to heterogeneous databases with matching dependencies for schema alignment and similarity-based matches. Sampling sharpens learning efficiency while yielding accurate Datalog definitions of the target relation. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11712
Venue
VLDB
Year
2018
Pagerank
4.1945683e-05
Overall Rank
11,742 | 18.32%
DOI
10.14778/3229863.3236261

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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
702 Reasoning about Record Matching Rules 2009 VLDB 0.00017918203
903 To Join or Not to Join? Thinking Twice about Joins before Feature Selection 2016 SIGMOD 0.0001547016
7,664 Schema Independent Relational Learning 2017 SIGMOD 4.6857329e-05
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