Efficient, robust and effective rank aggregation for massive biological datasets-Reference-Cited by-同舟云学术

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Efficient, robust and effective rank aggregation for massive biological datasets

Published:2021-11 Issue: Volume:124 Page:406-421
ISSN:0167-739X
Container-title:Future Generation Computer Systems
language:en
Short-container-title:Future Generation Computer Systems

Author:

Andrieu Pierre,Brancotte Bryan^ORCID,Bulteau Laurent,Cohen-Boulakia Sarah,Denise Alain^ORCID,Pierrot Adeline,Vialette Stéphane

Publisher

Elsevier BV

Subject

Computer Networks and Communications,Hardware and Architecture,Software

Reference45 articles.

1. Entrez gene: gene-centered information at NCBI;Maglott;Nucleic Acids Res.,2005

2. Rank aggregation methods for the web;Dwork,2001

3. Theoretical and empirical evaluation of data reduction for exact kemeny rank aggregation;Betzler;Auton. Agents Multi-Agent Syst.,2013

4. Handbook of Social Choice and Welfare, Vol. 1;Arrow,2002

5. Conqur-bio: Consensus ranking with query reformulation for biological data;Brancotte,2014

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A unifying rank aggregation framework to suitably and efficiently aggregate any kind of rankings;International Journal of Approximate Reasoning;2023-11

2. Beyond kemeny rank aggregation: A parameterizable-penalty framework for robust ranking aggregation with ties;Omega;2023-09

3. Measuring robustness in rank aggregation based on the error-effectiveness curve;Information Processing & Management;2023-07

4. Integer Linear Programming Reformulations for the Linear Ordering Problem;Communications in Computer and Information Science;2022

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