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Rank aggregation with ties: Experiments and Analysis

Summary: First large-scale study of rank aggregation with ties: reviews tie-handling algorithms and presents the first exact solver. Large-scale empirical evaluation on real and synthetic data shows when to prefer each method based on dataset features. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10999
Venue
VLDB
Year
2015
Pagerank
5.365274e-05
Overall Rank
5,700 | 60.35%
DOI
-

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
7,632 Rank Aggregation with Proportionate Fairness 2022 SIGMOD 4.6915165e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 5 of 5 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
709 Efficient Similarity Search and Classification via Rank Aggregation 2003 SIGMOD 0.00017768547
2,385 Comparing and Aggregating Rankings with Ties 2004 PODS 8.9247846e-05
4,803 A System for Management and Analysis of Preference Data 2014 VLDB 5.9107061e-05
7,009 Understanding local structure in ranked datasets 2013 CIDR 4.8637193e-05
8,764 Similarity Search for Scientific Workflows 2014 VLDB 4.456315e-05
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