scholarly journals Comparing Rank Aggregation Methods based on Mallows Model

2019 ◽  
Author(s):  
Zhangqian Zhu ◽  
Xiaomeng Wang ◽  
Shigang Qiu
Keyword(s):  
Rank Aggregation ◽  
Aggregation Methods ◽  
Mallows Model

Rank aggregation methods dealing with ordinal uncertain preferences

2017 ◽  
Vol 78 ◽  
pp. 103-109 ◽  
Author(s):  
Esther Dopazo ◽  
María L. Martínez-Céspedes
Keyword(s):  
Rank Aggregation ◽  
Aggregation Methods ◽  
Uncertain Preferences

scholarly journals Unsupervised Rank Fusion for Diverse Image Metasearch

2019 ◽  
Author(s):  
José Solenir L. Figuerêdo ◽  
Rodrigo Tripodi Calumby
Keyword(s):  
Image Retrieval ◽  
Search Engines ◽  
Rank Aggregation ◽  
Aggregation Methods ◽  
Experimental Findings ◽  
The Impact

For a given query and a set of images ranked lists retrieved from multiple search engines, the metasearch technique aims at combining these lists to build an unified ranking with improved relevance. Rank aggregation is an approach that has been widely used to support this task. This paper investigates the use of rank aggregation methods in the metasearch scenario for diverse image retrieval. Although metasearch systems are usually driven by the relevance of the final result, the impact on diversification has also been analyzed. The experimental findings suggest metasearch based on rank aggregation allows significant improvements, both in terms of relevance and diversity.

Rank aggregation methods comparison: A case for triage prioritization

2013 ◽  
Vol 40 (4) ◽  
pp. 1305-1311 ◽  
Author(s):  
Erica B. Fields ◽  
Gül E. Okudan ◽  
Omar M. Ashour
Keyword(s):  
Rank Aggregation ◽  
Methods Comparison ◽  
Aggregation Methods

scholarly journals Partition-Mallows Model and Its Inference for Rank Aggregation

2021 ◽  
pp. 1-41
Author(s):  
Wanchuang Zhu ◽  
Yingkai Jiang ◽  
Jun S. Liu ◽  
Ke Deng
Keyword(s):  
Rank Aggregation ◽  
Mallows Model

scholarly journals How Similar Are Two Elections?

2019 ◽  
Vol 33 ◽  
pp. 1909-1916 ◽  
Author(s):  
Piotr Faliszewski ◽  
Piotr Skowron ◽  
Arkadii Slinko ◽  
Stanisław Szufa ◽  
Nimrod Talmon
Keyword(s):  
Polynomial Time ◽  
Isomorphism Problem ◽  
Rank Aggregation ◽  
Aggregation Methods ◽  
Preference Orders

We introduce the ELECTION ISOMORPHISM problem and a family of its approximate variants, which we refer to as dISOMORPHISM DISTANCE (d-ID) problems (where d is a metric between preference orders). We show that ELECTION ISOMORPHISM is polynomial-time solvable, and that the d-ISOMORPHISM DISTANCE problems generalize various classic rank-aggregation methods (e.g., those of Kemeny and Litvak). We establish the complexity of our problems (including their inapproximability) and provide initial experiments regarding the ability to solve them in practice.

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