caa a22 4500 445871458 CHVBK 20180317145513.0 cr unu---uuuuu 170323e20110101xx s 000 0 eng 10.1007/s10618-010-0175-9 doi (NATIONALLICENCE)springer-10.1007/s10618-010-0175-9 A survey of hierarchical classification across different application domains [Elektronische Daten] [Carlos Silla Jr., Alex Freitas] 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. The Author(s), 2010 Hierarchical classification nationallicence Tree-structured class hierarchies nationallicence DAG-structured class hierarchies nationallicence Silla Jr. Carlos School of Computing, University of Kent, Canterbury, UK aut Freitas Alex School of Computing, University of Kent, Canterbury, UK aut Data Mining and Knowledge Discovery Springer US; http://www.springer-ny.com 22/1-2(2011-01-01), 31-72 1384-5810 22:1-2<31 2011 22 10618 https://doi.org/10.1007/s10618-010-0175-9 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10618-010-0175-9 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Silla Jr Carlos School of Computing, University of Kent, Canterbury, UK aut NATIONALLICENCE 700 1- Freitas Alex School of Computing, University of Kent, Canterbury, UK aut NATIONALLICENCE 773 0- Data Mining and Knowledge Discovery Springer US; http://www.springer-ny.com 22/1-2(2011-01-01), 31-72 1384-5810 22:1-2<31 2011 22 10618 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer