Sciweavers

Share
PKDD
2015
Springer

Study on Meta-Learning Approach Application in Rank Aggregation Algorithm Selection

3 years 6 months ago
Study on Meta-Learning Approach Application in Rank Aggregation Algorithm Selection
Rank aggregation is an important task in many areas, nevertheless, none of rank aggregation algorithms is best for all cases. The main goal of this work is to develop a method, which for a given rank list finds the best rank aggregation algorithm with respect to a certain optimality criterion. Two approaches based on meta-feature description are proposed and one of them shows promising results.
Alexey Zabashta, Ivan Smetannikov, Andrey Filchenk
Added 16 Apr 2016
Updated 16 Apr 2016
Type Journal
Year 2015
Where PKDD
Authors Alexey Zabashta, Ivan Smetannikov, Andrey Filchenkov
Comments (0)
books