Discovering Bucket Orders from Full Rankings
Summary: Introduces Bucket Gap and Abnormal Rank Gap to discover bucket orders from noisy full rankings, reframing from a representative to an approximation perspective. Leverages inter-bucket dissimilarity and cross-quantile closeness; outperforms Bucket Pivot with ~30% lower error and ~50% noise tolerance. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Jianlin Feng (Huazhong University of Science and Technology; University of Illinois Urbana-Champaign)
- 2. Qiong Fang (Hong Kong University of Science and Technology)
- 3. Wilfred Ng (Hong Kong University of Science and Technology)
BibTeX Citation
@inproceedings{feng_sigmod08,
title = {{Discovering Bucket Orders from Full Rankings}},
author = {Feng, Jianlin and Fang, Qiong and Ng, Wilfred},
series = {{SIGMOD} '08},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/1376616.1376625},
url = {https://dl.acm.org/doi/10.1145/1376616.1376625},
year = {2008}
}
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| Rank | Cited Paper | Year | Venue | Pagerank |
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| 690 | Efficient Similarity Search and Classification via Rank Aggregation | 2003 | SIGMOD | 0.0001492934 |
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