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Методы агрегирования рангов×Модель Брэдли-Терри×
ОбластьПринятие решенийПринятие решений
СемействоMachine learningRegression model
Год появления20011952
Автор методаDwork, Kumar, Naor & SivakumarRalph Bradley & Milton Terry
ТипCombinatorial ranking methodProbabilistic paired comparison model
Основополагающий источникDwork, C., Kumar, R., Naor, M., & Sivakumar, D. (2001). Rank aggregation methods for the web. Proceedings of the 10th International Conference on World Wide Web, 613–622. DOI ↗Bradley, R. A., & Terry, M. E. (1952). Rank analysis of incomplete block designs: I. The method of paired comparisons. Biometrika, 39(3/4), 324–345. DOI ↗
Другие названияRank Fusion, Order Aggregation, Preference Aggregation, Sıralama BirleştirmeBT Model, Bradley-Terry-Luce Model, Paired Comparison Model, İkili Karşılaştırma Modeli
Связанные23
СводкаRank Aggregation is a family of methods that combine multiple ranked lists of alternatives into a single consensus ranking. Formally studied in the context of web search by Dwork, Kumar, Naor, and Sivakumar (2001), these methods address the problem of synthesizing divergent preference orderings from multiple sources — such as search engines, expert judges, or voter ballots — into one coherent, representative ordering that minimizes overall disagreement across the input rankings.The Bradley-Terry model is a probabilistic model for paired comparisons that assigns a latent strength parameter to each item and predicts the probability that one item beats another in a head-to-head contest. Introduced by Ralph A. Bradley and Milton E. Terry in 1952, it provides a principled statistical framework for ranking items from pairwise preference data, including incomplete comparison designs where not every pair is directly observed.
ScholarGateНабор данных
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  2. 1 Источники
  3. PUBLISHED
  1. v1
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ScholarGateСравнение методов: Rank Aggregation · Bradley-Terry Model. Получено 2026-06-18 из https://scholargate.app/ru/compare