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
Short communication: An impossibility theorem for indicators aggregation
Fuzzy Sets and Systems
A Multi-Criteria Decision Method Based on Rank Distance
Fundamenta Informaticae
A Generalization of the Assignment Problem, and its Application to the Rank Aggregation Problem
Fundamenta Informaticae
Pastiche detection based on stopword rankings: exposing impersonators of a Romanian writer
EACL 2012 Proceedings of the Workshop on Computational Approaches to Deception Detection
Local patch dissimilarity for images
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part I
Clustering based on rank distance with applications on DNA
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part V
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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.