Decision Combination in Multiple Classifier Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
A comparison of classifiers and document representations for the routing problem
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Foundations of statistical natural language processing
Foundations of statistical natural language processing
Machine Learning
An efficient approach for the rank aggregation problem
Theoretical Computer Science
A Generalization of the Assignment Problem, and its Application to the Rank Aggregation Problem
Fundamenta Informaticae
A Multi-Criteria Decision Method Based on Rank Distance
Fundamenta Informaticae
LD '06 Proceedings of the Workshop on Linguistic Distances
Meta-search: aggregating search engine results using rank-distance
Proceedings of the Fourth International Conference on SImilarity Search and APplications
On the syllabic similarities of romance languages
CICLing'05 Proceedings of the 6th international conference on Computational Linguistics and Intelligent Text Processing
Rank distance aggregation as a fixed classifier combining rule for text categorization
CICLing'10 Proceedings of the 11th international conference on Computational Linguistics and Intelligent Text Processing
A note on permutations and rank aggregation
Mathematical and Computer Modelling: An International Journal
On the closest string via rank distance
CPM'12 Proceedings of the 23rd Annual conference on Combinatorial Pattern Matching
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In this paper we present an aggregation method which can be applied to classifications having different vocabularies. The method uses the rank distance (Dinu, 2003), a metric which measures the similarity between two hierarchies based on the ranks of objects. We define the aggregation of n hierarchies as the classification for which the sum of distances from it to each of the n hierarchies is minimal. We study some of his rationality properties and propose some open problems.