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Reconciling Schemas of Disparate Data Sources: A Machine-Learning Approach

Summary: Introduces LSD, a semi-automatic data integration system that learns semantic mappings to a schema from seed mappings. It combines multiple learners—using schema, data, domain constraints, and XML structure—with a meta-learner to map sources. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3357
Venue
SIGMOD
Year
2001
Pagerank
0.0002305693
Overall Rank
263 | 98.20%
DOI
10.1145/375663.375731

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{doan_sigmod01,
        title = {{Reconciling Schemas of Disparate Data Sources: A Machine-Learning Approach}},
        author = {Doan, AnHai and Domingos, Pedro and Halevy, Alon},
        series = {{SIGMOD} '01},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/375663.375731},
        url = {https://dl.acm.org/doi/10.1145/375663.375731},
        year = {2001}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 52 citing papers.

Rank Citing Paper Year Venue Pagerank
12,739 SMART: A Tool for Semantic-Driven Creation of Complex XML Mappings 2005 SIGMOD 5.093636e-05
12,826 Schema-driven Customization of Web Services 2003 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 5 of 5 cited papers.

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

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