Rank aggregation methods for the Web
Proceedings of the 10th international conference on World Wide Web
Parameterized Complexity Theory (Texts in Theoretical Computer Science. An EATCS Series)
Parameterized Complexity Theory (Texts in Theoretical Computer Science. An EATCS Series)
The complexity of Kemeny elections
Theoretical Computer Science
Proceedings of the thirty-ninth annual ACM symposium on Theory of computing
Multiple genome rearrangement by swaps and by element duplications
Theoretical Computer Science
On the Approximation of Correlation Clustering and Consensus Clustering
Journal of Computer and System Sciences
Aggregating inconsistent information: Ranking and clustering
Journal of the ACM (JACM)
Pattern matching with address errors: Rearrangement distances
Journal of Computer and System Sciences
Computing slater rankings using similarities among candidates
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Improved bounds for computing Kemeny rankings
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Deterministic Pivoting Algorithms for Constrained Ranking and Clustering Problems
Mathematics of Operations Research
Fixed-parameter algorithms for Kemeny rankings
Theoretical Computer Science
Closest Substring Problems with Small Distances
SIAM Journal on Computing
Improved Parameterized Algorithms for the Kemeny Aggregation Problem
Parameterized and Exact Computation
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We propose an effective polynomial-time preprocessing strategy for intractable median problems. Developing a new methodological framework, we show that if the input instances of generally intractable problems exhibit a sufficiently high degree of similarity between each other on average, then there are efficient exact solving algorithms. In other words, we show that the median problems Swap Median Permutation, Consensus Clustering, Kemeny Score, and Kemeny Tie Score all are fixed-parameter tractable with respect to the parameter “average distance between input objects”. To this end, we develop the new concept of “partial kernelization” and identify interesting polynomial-time solvable special cases for the considered problems.