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Distributed Representations of Tuples for Entity Resolution

Summary: DeepER encodes entire tuples as task-specific distributed representations via uni-/bidirectional LSTM RNNs, reducing labeling and feature engineering. An all-attribute LSH blocker yields compact candidate sets, delivering accurate, efficient ER across benchmark, biomedical, and multilingual data. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
11821
Venue
VLDB
Year
2018
Pagerank
0.0001761456
Overall Rank
489 | 96.65%
DOI
10.14778/3236187.3236198

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Authors

BibTeX Citation

@article{ebraheem_vldb18,
        title = {{Distributed Representations of Tuples for Entity Resolution}},
        author = {Ebraheem, Muhammad and Thirumuruganathan, Saravanan and Joty, Shafiq and Ouzzani, Mourad and Tang, Nan},
        journal = {PVLDB},
        series = {{VLDB} '18},
        volume = {11},
        number = {11},
        pages = {1454--1467},
        doi = {10.14778/3236187.3236198},
        url = {https://doi.org/10.14778/3236187.3236198},
        year = {2018}
}

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