A Topic-based Reviewer Assignment System
Summary: RAS automatically extracts topic vectors for papers and reviewers, enabling bid-free reviewer assignment. It supports models (stable marriage, optimal assignment) and a novel coverage-maximizing model, with a demonstrator for profiling and comparison. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Ngai Meng Kou (University of Macau)
- 2. Leong Hou U (University of Macau)
- 3. Nikos Mamoulis (University of Hong Kong)
- 4. Yuhong Li (University of Macau)
- 5. Ye Li (University of Macau)
- 6. Zhiguo Gong (University of Macau)
BibTeX Citation
@article{kou_vldb15,
title = {{A Topic-based Reviewer Assignment System}},
author = {Kou, Ngai Meng and U, Leong Hou and Mamoulis, Nikos and Li, Yuhong and Li, Ye and Gong, Zhiguo},
journal = {PVLDB},
series = {{VLDB} '15},
volume = {8},
number = {12},
pages = {1852--1855},
doi = {10.14778/2824032.2824084},
url = {https://doi.org/10.14778/2824032.2824084},
year = {2015}
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 13,576 | Weighted Coverage based Reviewer Assignment | 2015 | SIGMOD | - |
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