Splitting Tuples of Mismatched Entities
Summary: Inverse ER: split tuples that merge distinct entities into separate records. Proposes a rule-based tuple-splitting scheme with ML for attribute correlation and missing-value imputation, using cross-relational alignment and knowledge-graph data to reach ~0.92 F-measure. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Wenfei Fan (Beihang University; Shenzhen University; University of Edinburgh)
- 2. Ziyan Han (Beihang University)
- 3. Weilong Ren (Shenzhen University)
- 4. Ding Wang (Tsinghua University)
- 5. Yaoshu Wang (Shenzhen University)
- 6. Min Xie (Shenzhen University)
- 7. Mengyi Yan (Beihang University)
BibTeX Citation
@inproceedings{fan_sigmod23,
title = {{Splitting Tuples of Mismatched Entities}},
author = {Fan, Wenfei and Han, Ziyan and Ren, Weilong and Wang, Ding and Wang, Yaoshu and Xie, Min and Yan, Mengyi},
series = {{SIGMOD} '23},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3626763},
url = {https://dl.acm.org/doi/10.1145/3626763},
year = {2023}
}Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,876 | Rock: Cleaning Data by Embedding ML in Logic Rules | 2024 | SIGMOD | 5.4336606e-05 |
| 11,197 | Incremental Rule Discovery in Response to Parameter Updates | 2025 | SIGMOD | 4.9769913e-05 |
| 11,596 | Enriching Relations with Additional Attributes for ER | 2024 | VLDB | 4.9769913e-05 |
| 11,641 | Rock: Cleaning Data with both ML and Logic Rules | 2024 | VLDB | 4.9769913e-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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