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طرق تجميع الرتب×نموذج بلاكيت-لوس×
المجالاتخاذ القراراتخاذ القرار
العائلةMachine learningRegression model
سنة النشأة20011975
صاحب الطريقةDwork, Kumar, Naor & SivakumarRobin Plackett; R. Duncan Luce
النوعCombinatorial ranking methodProbabilistic ranking model
المصدر التأسيسيDwork, 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 ↗Plackett, R. L. (1975). The analysis of permutations. Journal of the Royal Statistical Society: Series C, 24(2), 193–202. DOI ↗
الأسماء البديلةRank Fusion, Order Aggregation, Preference Aggregation, Sıralama BirleştirmeLuce's Choice Axiom Model, Rank-Ordered Logit Model, Exploded Logit Model, Sıralama Tercih Modeli
ذات صلة23
الملخصRank 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 Plackett-Luce model is a probabilistic framework for analysing and predicting rank-ordered data. Introduced by Robin Plackett (1975) — building on R. Duncan Luce's earlier axiom of choice (1959) — it models the probability of any complete ranking of items as a sequential selection process, where each item's chance of being chosen at each position is proportional to its latent worth parameter. It is widely used in preference learning, recommender systems, and choice modelling.
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ScholarGateقارن الطرق: Rank Aggregation · Plackett-Luce Model. استُرجع بتاريخ 2026-06-18 من https://scholargate.app/ar/compare