G. Tsoumakas, and I. Katakis. International Journal of Data Warehouse and Mining, 3 (3):
1--13(2007)
Abstract
Nowadays, multi-label classification methods are increasingly required by modern applications, such as protein function classification, music categorization and semantic scene classification. This paper introduces the task of multi-label classification, organizes the sparse related literature into a structured presentation and performs comparative experimental results of certain multi-label classification methods. It also contributes the definition of concepts for the quantification of the multi-label nature of a data set.
Description
CiteULike: Multi Label Classification: An Overview
%0 Journal Article
%1 citeulike:2146554
%A Tsoumakas, G.
%A Katakis, I.
%D 2007
%E Taniar, David
%I Idea Group Publishing
%J International Journal of Data Warehouse and Mining
%K classification learning machine ml multi_label survey
%N 3
%P 1--13
%T Multi Label Classification: An Overview
%V 3
%X Nowadays, multi-label classification methods are increasingly required by modern applications, such as protein function classification, music categorization and semantic scene classification. This paper introduces the task of multi-label classification, organizes the sparse related literature into a structured presentation and performs comparative experimental results of certain multi-label classification methods. It also contributes the definition of concepts for the quantification of the multi-label nature of a data set.
@article{citeulike:2146554,
abstract = {Nowadays, multi-label classification methods are increasingly required by modern applications, such as protein function classification, music categorization and semantic scene classification. This paper introduces the task of multi-label classification, organizes the sparse related literature into a structured presentation and performs comparative experimental results of certain multi-label classification methods. It also contributes the definition of concepts for the quantification of the multi-label nature of a data set.},
added-at = {2009-03-23T21:50:27.000+0100},
author = {Tsoumakas, G. and Katakis, I.},
biburl = {https://www.bibsonomy.org/bibtex/252c3b18481f5146e4c213d609c1143fc/hotho},
citeulike-article-id = {2146554},
description = {CiteULike: Multi Label Classification: An Overview},
editor = {Taniar, David},
interhash = {f8e6c4b6b3df7461d070a1a9cc1d15c1},
intrahash = {52c3b18481f5146e4c213d609c1143fc},
journal = {International Journal of Data Warehouse and Mining},
keywords = {classification learning machine ml multi_label survey},
number = 3,
pages = {1--13},
posted-at = {2007-12-19 13:38:29},
priority = {2},
publisher = {Idea Group Publishing},
timestamp = {2009-03-23T21:50:27.000+0100},
title = {Multi Label Classification: An Overview},
volume = 3,
year = 2007
}