, Volume 57, Issue 2, pp 284–300 | Cite as

Aggregation of Partial Rankings, p-Ratings and Top-m Lists

  • Nir AilonEmail author


We study the problem of aggregating partial rankings. This problem is motivated by applications such as meta-searching and information retrieval, search engine spam fighting, e-commerce, learning from experts, analysis of population preference sampling, committee decision making and more. We improve recent constant factor approximation algorithms for aggregation of full rankings and generalize them to partial rankings. Our algorithms improve constant factor approximation with respect to a family of metrics recently proposed in the context of comparing partial rankings. We pay special attention to two important types of partial rankings: the well-known top-m lists and the more general p-ratings which we define. We provide first evidence for hardness of aggregating them for constant mp.


Rank aggregation Ranking with ties Approximation algorithms 


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Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  1. 1.Google ResearchNew YorkUSA

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