A randomized approximation algorithm for computing bucket orders

Authors:
Antti Ukkonen;Kai Puolamäki;Aristides Gionis;Heikki Mannila
Affiliations:
Helsinki Institute for Information Technology HIIT, Finland and Helsinki University of Technology, Department of Information and Computer Science, P.O. Box 5400, Helsinki, Finland;Helsinki Institute for Information Technology HIIT, Finland and Helsinki University of Technology, Department of Information and Computer Science, P.O. Box 5400, Helsinki, Finland;Yahoo! Research Barcelona, Spain;Helsinki Institute for Information Technology HIIT, Finland and Helsinki University of Technology, Department of Information and Computer Science, P.O. Box 5400, Helsinki, Finland and University o ...
Venue:
Information Processing Letters
Year:
2009

Citing 5
Cited 1

Computers and Intractability: A Guide to the Theory of NP-Completeness

Computers and Intractability: A Guide to the Theory of NP-Completeness
Aggregating inconsistent information: ranking and clustering

Proceedings of the thirty-seventh annual ACM symposium on Theory of computing
Ordering by weighted number of wins gives a good ranking for weighted tournaments

SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Algorithms for discovering bucket orders from data

Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
How to rank with few errors

Proceedings of the thirty-ninth annual ACM symposium on Theory of computing

Rank quantization

Proceedings of the sixth ACM international conference on Web search and data mining

Quantified Score

Hi-index	0.89

Visualization

Abstract

We show that a simple randomized algorithm has an expected constant factor approximation guarantee for fitting bucket orders to a set of pairwise preferences.