Smurf: Self-Service String Matching Using Random Forests
Summary: Smurf enables self-service string matching with active learning, reducing labeling by 43–76% while maintaining F1. Its RDBMS-style plan optimization reuses computations across RF trees for two string sets, advancing self-service SM and scalable RF over structured data. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Paul Suganthan G. C. (University of Wisconsin)
- 2. Adel Ardalan (University of Wisconsin)
- 3. AnHai Doan (University of Wisconsin)
- 4. Aditya Akella (University of Wisconsin)
BibTeX Citation
@article{c_vldb19,
title = {{Smurf: Self-Service String Matching Using Random Forests}},
author = {C., Paul Suganthan G. and Ardalan, Adel and Doan, AnHai and Akella, Aditya},
journal = {PVLDB},
series = {{VLDB} '19},
volume = {12},
number = {3},
pages = {278--291},
doi = {10.14778/3291264.3291272},
url = {https://doi.org/10.14778/3291264.3291272},
year = {2019}
}
Incoming Citations (Sorted by Pagerank)
Showing 8 of 8 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,391 | Creating Embeddings of Heterogeneous Relational Datasets for Data Integration Tasks | 2020 | SIGMOD | 0.00010816237 |
| 3,473 | Unicorn: A Unified Multi-tasking Model for Supporting Matching Tasks in Data Integration | 2023 | SIGMOD | 7.2728706e-05 |
| 7,068 | How do Categorical Duplicates Affect ML? A New Benchmark and Empirical Analyses | 2024 | VLDB | 5.6083188e-05 |
| 7,509 | Entity Matching Meets Data Science: A Progress Report from the Magellan Project | 2019 | SIGMOD | 5.5062607e-05 |
| 9,608 | Discovering Top-k Rules using Subjective and Objective Criteria | 2023 | SIGMOD | 5.1527671e-05 |
| 11,188 | Incremental Rule Discovery in Response to Parameter Updates | 2025 | SIGMOD | 4.9793485e-05 |
| 11,615 | Dealing with Acronyms, Abbreviations, and Typos in Real-World Entity Matching | 2024 | VLDB | 4.9793485e-05 |
| 11,988 | Shahin: Faster Algorithms for Generating Explanations for Multiple Predictions | 2021 | SIGMOD | 4.9793485e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 25 of 25 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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