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Machine Learning for Data Management: Problems and Solutions

Summary: Tractable Markov logic for data management models non-i.i.d., multi-relational data with convex parameter learning and ILP-based structure learning. Inference via probabilistic theorem proving enables exact, subsecond queries on an RDBMS-backed knowledge base, with applications to entity resolution, schema matching, ontology alignment, and information extraction. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5591
Venue
SIGMOD
Year
2018
Pagerank
4.4755972e-05
Overall Rank
8,637 | 39.98%
DOI
10.1145/3183713.3199515

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Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
7,868 Learning Over Dirty Data Without Cleaning 2020 SIGMOD 4.6276013e-05
9,885 Scalable and Usable Relational Learning With Automatic Language Bias 2021 SIGMOD 4.2580321e-05
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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