A survey of hierarchical classification across different application domains

Authors:
Carlos N. Silla, Jr.;Alex A. Freitas
Affiliations:
School of Computing, University of Kent, Canterbury, UK;School of Computing, University of Kent, Canterbury, UK
Venue:
Data Mining and Knowledge Discovery
Year:
2011

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Abstract

In this survey we discuss the task of hierarchical classification. The literature about this field is scattered across very different application domains and for that reason research in one domain is often done unaware of methods developed in other domains. We define what is the task of hierarchical classification and discuss why some related tasks should not be considered hierarchical classification. We also present a new perspective about some existing hierarchical classification approaches, and based on that perspective we propose a new unifying framework to classify the existing approaches. We also present a review of empirical comparisons of the existing methods reported in the literature as well as a conceptual comparison of those methods at a high level of abstraction, discussing their advantages and disadvantages.