Web Record Extraction with Invariants
Summary: Introduce invariants for Web data records to relax prior assumptions of uniform schemas and linear layouts, enabling discovery of heterogeneous, nested records on modern pages. Propose Miria, a bottom-up recursive algorithm that reconstructs records from invariants and outperforms prior extractors. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zhijia Chen (Temple University)
- 2. Weiyi Meng (Binghamton University)
- 3. Eduard Dragut (Temple University)
BibTeX Citation
@article{chen_vldb23,
title = {{Web Record Extraction with Invariants}},
author = {Chen, Zhijia and Meng, Weiyi and Dragut, Eduard},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {4},
pages = {959--972},
doi = {10.14778/3574245.3574276},
url = {https://doi.org/10.14778/3574245.3574276},
year = {2023}
}
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,454 | Visual Template Inference for Data Extraction from Documents | 2026 | SIGMOD | 5.0723324e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 12 of 12 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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