OpenMEL: Unsupervised Multimodal Entity Linking Using Noise-Free Expanded Queries and Global Coherence
Summary: OpenMEL performs unsupervised multimodal entity linking by enriching sparse text and adaptively selecting multi-level visual inputs to suppress noise. A bounded-node maximum-spanning-tree cover captures global KB entity coherence, optimized greedily with theoretical guarantees. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Xinyi Zhu (Hong Kong University of Science and Technology)
- 2. Yongqi Zhang (Hong Kong University of Science and Technology)
- 3. Lei Chen (Hong Kong University of Science and Technology)
BibTeX Citation
@article{zhu_vldb25,
title = {{OpenMEL: Unsupervised Multimodal Entity Linking Using Noise-Free Expanded Queries and Global Coherence}},
author = {Zhu, Xinyi and Zhang, Yongqi and Chen, Lei},
journal = {PVLDB},
series = {{VLDB} '25},
volume = {18},
number = {8},
pages = {2454--2467},
doi = {10.14778/3742728.3742740},
url = {https://doi.org/10.14778/3742728.3742740},
year = {2025}
}
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,980 | Query-Driven On-The-Fly Knowledge Base Construction | 2018 | VLDB | 7.7875217e-05 |
| 3,031 | Entity Search Engine: Towards Agile Best-Effort Information Integration over the Web | 2007 | CIDR | 7.7351469e-05 |
| 4,148 | A Benchmarking Study of Embedding-based Entity Alignment for Knowledge Graphs | 2020 | VLDB | 6.7803412e-05 |
| 4,365 | Measure-driven Keyword-Query Expansion | 2009 | VLDB | 6.6337428e-05 |
| 4,952 | KBPearl: A Knowledge Base Population System Supported by Joint Entity and Relation Linking | 2020 | VLDB | 6.3417814e-05 |
| 8,456 | Experiments on Query Expansion for Internet Yellow Page Services Using Web Log Mining | 2002 | VLDB | 5.3350162e-05 |
| 11,980 | TENET: Joint Entity and Relation Linking with Coherence Relaxation | 2021 | SIGMOD | 4.9793485e-05 |
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