DBScholar

Back to papers

A Comprehensive Benchmark Framework for Active Learning Methods in Entity Matching

Summary: Unifies active learning for Entity Matching into a benchmark framework to compose learning and selection strategies. On public EM data, active learning with fewer labels can match or beat supervised results; optimizations boost F1 ~9% and cut latency up to 10x. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5872
Venue
SIGMOD
Year
2020
Pagerank
8.5486912e-05
Overall Rank
2,463 | 83.11%
DOI
10.1145/3318464.3380597

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{meduri_sigmod20,
        title = {{A Comprehensive Benchmark Framework for Active Learning Methods in Entity Matching}},
        author = {Meduri, Vamsi and Popa, Lucian and Sen, Prithviraj and Sarwat, Mohamed},
        series = {{SIGMOD} '20},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3318464.3380597},
        url = {https://dl.acm.org/doi/10.1145/3318464.3380597},
        year = {2020}
}

Incoming Citations (Sorted by Pagerank)

Showing 15 of 15 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 15 of 15 cited papers.

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

Previous Page 1 / 1 Next

Semantically Similar Papers