Parallel Discrepancy Detection and Incremental Detection
Summary: Parallel discrepancy detection for duplicates, mismatches, and conflicts via ML-embed rules, unifying ER and conflict handling. Parallel and incremental algorithms offer scalability; NP-hard, W[1]-hard; bounded incremental; validated on real/synthetic data. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Wenfei Fan (Shenzhen University; University of Edinburgh)
- 2. Chao Tian (Alibaba)
- 3. Yanghao Wang (University of Edinburgh)
- 4. Qiang Yin (Alibaba)
BibTeX Citation
@article{fan_vldb21,
title = {{Parallel Discrepancy Detection and Incremental Detection}},
author = {Fan, Wenfei and Tian, Chao and Wang, Yanghao and Yin, Qiang},
journal = {PVLDB},
series = {{VLDB} '21},
volume = {14},
number = {8},
pages = {1351--1364},
doi = {10.14778/3457390.3457400},
url = {https://doi.org/10.14778/3457390.3457400},
year = {2021}
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