Skip to Main content Skip to Navigation
Conference papers

Ranking Constraints

Abstract : We need to reason about rankings of objects in a wide variety of domains including information retrieval, sports tournaments, bibliometrics, and statistics. We propose a global constraint therefore for modeling rankings. One important application for rankings is in reasoning about the correlation or uncorrelation between sequences. For example, we might wish to have consecutive delivery sched- ules correlated to make it easier for clients and em- ployees, or uncorrelated to avoid predictability and complacence. We therefore also consider global correlation constraints between rankings. For both ranking and correlation constraints, we propose efficient filtering algorithms and decompositions, and report experimental results demonstrating the promise of our proposed approach.
Document type :
Conference papers
Complete list of metadata

Cited literature [15 references]  Display  Hide  Download
Contributor : Joël Quinqueton Connect in order to contact the contributor
Submitted on : Friday, September 30, 2016 - 9:26:02 PM
Last modification on : Wednesday, October 27, 2021 - 12:16:31 PM
Long-term archiving on: : Saturday, December 31, 2016 - 4:39:47 PM


Files produced by the author(s)


Distributed under a Creative Commons Attribution 4.0 International License


  • HAL Id : lirmm-01374715, version 1
  • PRODINRA : 406714


Christian Bessière, Emmanuel Hébrard, George Katsirelos, Toby Walsh, Zeynep Kiziltan. Ranking Constraints
. IJCAI: International Joint Conference on Artificial Intelligence, Jul 2016, New York City, United States. pp.705-711. ⟨lirmm-01374715⟩



Record views


Files downloads