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@inproceedings{read2011streaming,
  title={Streaming Multi-label Classification.},
  author={<NAME> <NAME> <NAME> <NAME>},
  booktitle={WAPA},
  pages={19--25},
  year={2011}
}
@article{read2012scalable,
  title={Scalable and Efficient Multi-Label Classification for Evolving Data Streams},
  author={<NAME> and <NAME> and <NAME> and <NAME>},
  journal={Machine Learning},
  volume={88},
  number={1-2},
  pages={243--272},
  year={2012},
  publisher={Springer}
}
@inproceedings{read2009classifier,
  title={Classifier Chains for Multi-Label Classification},
  author={<NAME> <NAME> <NAME> <NAME>},
  booktitle={Joint European Conference on Machine Learning and Knowledge Discovery in Databases},
  pages={254--269},
  year={2009},
  organization={Springer}
}
@inproceedings{bifet2011moa,
  title={{MOA}: A Real-Time Analytics Open Source Framework},
  author={<NAME> and <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and <NAME>},
  booktitle={ECML PKDD},
  pages={617--620},
  year={2011},
  organization={Springer}
}
@mastersthesis{asl2016goowe,
  title={{GOOWE}: Geometrically Optimum and Online-Weighted Ensemble Classifier for Evolving Data Streams},
  author={Asl-Bonab, <NAME>},
  year={2016},
  school={Bilkent University}
}
@inproceedings{parkfurnkranz2008labelconst,
  title={Multi-label Classification with Label Constraints},
  author={<NAME> and <NAME>},
  booktitle={Proceedings of the Proceedings of the ECML/PKDD-08 Workshop on Preference Learning (PL-08)},
  pages={157--171},
  year={2008},
  organization={Citeseer}
}
@inproceedings{read2009generating,
  title={Generating Synthetic Multi-Label Data Streams},
  author={<NAME> and <NAME> and <NAME>},
  booktitle={ECML/PKKD 2009 Workshop on Learning from Multi-label Data (MLD’09)},
  pages={69--84},
  year={2009}
}
@article{cheng2009combining,
  title={Combining Instance-Based Learning and Logistic Regression for Multilabel Classification},
  author={<NAME> and <NAME>},
  journal={Machine Learning},
  volume={76},
  number={2-3},
  pages={211--225},
  year={2009},
  publisher={Springer}
}
@inproceedings{godbole2004discriminative,
  title={Discriminative Methods for Multi-Labeled Classification},
  author={<NAME> and <NAME>},
  booktitle={PAKDD},
  pages={22--30},
  year={2004},
  organization={Springer}
}
@article{hullermeier2008label,
  title={Label Ranking by Learning Pairwise Preferences},
  author={H{\"u}<NAME> and F{\"u}<NAME> and <NAME> and <NAME>},
  journal={Artificial Intelligence},
  volume={172},
  number={16},
  pages={1897--1916},
  year={2008},
  publisher={Elsevier}
}
@article{tsoumakas2006overview,
  title={Multi-Label Classification: An Overview},
  author={Tsoumakas, Grigorios and <NAME>},
  journal={International Journal of Data Warehousing and Mining},
  volume={3},
  number={3},
  year={2006}
}
@article{hall2009weka,
  title={The WEKA Data Mining software: An Update},
  author={<NAME> and <NAME> and <NAME> and Pfahringer, Bernhard and Reutemann, Peter and Witten, <NAME>},
  journal={ACM SIGKDD explorations newsletter},
  volume={11},
  number={1},
  pages={10--18},
  year={2009},
  publisher={ACM}
}
@article{read2016meka,
  title={MEKA: A Multi-label/Multi-target Extension to WEKA},
  author={<NAME> and Reutemann, Peter and <NAME> and <NAME>},
  journal={Journal of Machine Learning Research},
  volume={17},
  number={21},
  pages={1--5},
  year={2016}
}
@article{bifet2010moa,
  title={Moa: Massive Online Analysis},
  author={<NAME> and <NAME> and <NAME>},
  journal={Journal of Machine Learning Research},
  volume={11},
  number={May},
  pages={1601--1604},
  year={2010}
}
@inproceedings{qu2009mining,
  title={Mining Multi-Label Concept-Drifting Data Streams Using Dynamic Classifier Ensemble},
  author={<NAME> and <NAME> and <NAME> and <NAME>},
  booktitle={Asian Conference on Machine Learning},
  pages={308--321},
  year={2009},
  organization={Springer}
}
@article{zhang2014review,
  title={A Review on Multi-Label Learning Algorithms},
  author={<NAME> and <NAME>},
  journal={IEEE Transactions on Knowledge and Data Engineering},
  volume={26},
  number={8},
  pages={1819--1837},
  year={2014},
  publisher={IEEE}
}
 @inproceedings{tsoumakas2008effective,
  title={Effective and Efficient Multilabel Classification in Domains with Large Number of Labels},
  author={Tsoumakas, Grigorios and Katakis, Ioannis and Vlahavas, Ioannis},
  booktitle={Proc. ECML/PKDD 2008 Workshop on Mining Multidimensional Data (MMD’08)},
  pages={30--44},
  year={2008}
}
@article{tsoumakas2011rakel,
  title={Random k-Labelsets for Multilabel Classification},
  author={<NAME> and Katakis, Ioannis and Vlahavas, Ioannis},
  journal={IEEE Transactions on Knowledge and Data Engineering},
  volume={23},
  number={7},
  pages={1079--1089},
  year={2011},
  publisher={IEEE}
}
@article{gibaja2015tutorial,
  title={A Tutorial on Multilabel Learning},
  author={<NAME>},
  journal={ACM Computing Surveys (CSUR)},
  volume={47},
  number={3},
  pages={52},
  year={2015},
  publisher={ACM}
}
@article{zhang2007ml,
  title={ML-KNN: A Lazy Learning Approach to Multi-Label Learning},
  author={<NAME> and <NAME>},
  journal={Pattern Recognition},
  volume={40},
  number={7},
  pages={2038--2048},
  year={2007},
  publisher={Elsevier}
}
@inproceedings{kranen2012stream,
  title={Stream Data Mining Using the MOA Framework},
  author={<NAME> <NAME> <NAME> <NAME> <NAME> <NAME> <NAME> <NAME>},
  booktitle={International Conference on Database Systems for Advanced Applications},
  pages={309--313},
  year={2012},
  organization={Springer}
}
@article{Gomes:2017:SEL:3071073.3054925,
 author = {<NAME> <NAME> Enembreck, Fabr\'{\i}<NAME> <NAME>},
 title = {A Survey on Ensemble Learning for Data Stream Classification},
 journal = {ACM Comput. Surv.},
 issue_date = {May 2017},
 volume = {50},
 number = {2},
 month = mar,
 year = {2017},
 issn = {0360-0300},
 pages = {23:1--23:36},
 articleno = {23},
 numpages = {36},
 acmid = {3054925},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {Ensemble learning, data stream classification, supervised learning},
} 
% url = {http://doi.acm.org/10.1145/3054925},
% doi = {10.1145/3054925},
@techreport{sorower2010literature,
  title={A Literature Survey on Algorithms for Multi-Label Learning},
  author={<NAME>},
  institution={Oregon State University, Corvallis},
  year={2010}
}
@article{Krawczyk2017132,
title = "Ensemble Learning for Data Stream Analysis: A Survey ",
journal = "Information Fusion ",
volume = "37",
number = "",
pages = "132 - 156",
year = "2017",
note = "",
issn = "1566-2535",
author={Krawczyk, <NAME>, <NAME> and Gama, Joao and Stefanowski, Jerzy and Wo{\'z}niak, Micha{\l}},
keywords = "Ensemble learning",
keywords = "Data streams",
keywords = "Concept drift",
keywords = "Online learning",
keywords = "Non-stationary environments "
}%doi = "https://doi.org/10.1016/j.inffus.2017.02.004",
%url = "http://www.sciencedirect.com/science/article/pii/S1566253516302329",
@inproceedings{clare2001knowledge,
  title={Knowledge Discovery in Multi-Label Phenotype Data},
  author={<NAME> and King, <NAME>},
  booktitle={European Conference on Principles of Data Mining and Knowledge Discovery},
  pages={42--53},
  year={2001},
  organization={Springer}
}
@article{friedman1997bias,
  title={On Bias, Variance, 0/1—loss, and the Curse-of-Dimensionality},
  author={<NAME>},
  journal={Data mining and knowledge discovery},
  volume={1},
  number={1},
  pages={55--77},
  year={1997},
  publisher={Springer}
}
@inproceedings{freund1996experiments,
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  author={<NAME> and Schapire, <NAME> and others},
  booktitle={icml},
  volume={96},
  pages={148--156},
  year={1996}
}
@inproceedings{oza2005onlinebb,
  title={Online Bagging and Boosting},
  author={<NAME>},
  booktitle={2005 IEEE International Conference on Systems, Man and Cybernetics},
  volume={3},
  pages={2340--2345},
  year={2005},
  organization={IEEE}
}
@Inbook{Tsoumakas2010,
author="<NAME>
and Katakis, Ioannis
and Vlahavas, Ioannis",
editor="<NAME>
and <NAME>",
title="Mining Multi-label Data",
bookTitle="Data Mining and Knowledge Discovery Handbook",
year="2010",
publisher="Springer US",
address="Boston, MA",
pages="667--685",
abstract="A large body of research in supervised learning deals with the analysis of single-label data, where training examples are associated with a single label $\lambda$ from a set of disjoint labels L. However, training examples in several application domains are often associated with a set of labels Y ⊆ L. Such data are called multi-label.",
isbn="978-0-387-09823-4",
doi="10.1007/978-0-387-09823-4_34",
url="http://dx.doi.org/10.1007/978-0-387-09823-4_34"
}
@article{waegeman2014bayes,
  title={On the bayes-optimality of F-measure maximizers},
  author={<NAME> and Dembczy{\'<NAME> and H{\"u}<NAME>},
  journal={The Journal of Machine Learning Research},
  volume={15},
  number={1},
  pages={3333--3388},
  year={2014},
  publisher={JMLR. org}
}
@article{tahir2012multilabel,
  title={Multilabel classification using heterogeneous ensemble of multi-label classifiers},
  author={<NAME> <NAME> and <NAME>},
  journal={Pattern Recognition Letters},
  volume={33},
  number={5},
  pages={513--523},
  year={2012},
  publisher={Elsevier}
}
@inproceedings{read2008pruned,
  title={Multi-label Classification Using Ensembles of Pruned Sets},
  author={<NAME> and <NAME> and <NAME>},
  booktitle={The Eighth IEEE ICDM},
  pages={995--1000},
  year={2008},
  organization={IEEE}
}
@article{gibaja2014review,
  title={Multi-Label Learning: A Review of the State of the Art and Ongoing Research},
  author={<NAME> and <NAME>{\'a}n},
  journal={Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery},
  volume={4},
  number={6},
  pages={411--444},
  year={2014},
  publisher={Wiley Online Library}
}
@article{dietterich2000ensemble,
  title={Ensemble methods in machine learning},
  author={<NAME> and others},
  journal={Multiple classifier systems},
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  pages={1--15},
  year={2000},
  publisher={Springer}
}
@inproceedings{cheng2010pcc,
  title={Bayes optimal multilabel classification via probabilistic classifier chains},
  author={<NAME> and <NAME>},
  booktitle={Proceedings of the 27th international conference on machine learning (ICML-10)},
  pages={279--286},
  year={2010}
}
@article{read2015trellis,
  title={Scalable multi-output label prediction: From classifier chains to classifier trellises},
  author={<NAME> and <NAME> and <NAME> and <NAME>},
  journal={Pattern Recognition},
  volume={48},
  number={6},
  pages={2096--2109},
  year={2015},
  publisher={Elsevier}
}
@article{read2014montecarlo,
  title={Efficient monte carlo methods for multi-dimensional learning with classifier chains},
  author={<NAME> and <NAME> <NAME>},
  journal={Pattern Recognition},
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  number={3},
  pages={1535--1546},
  year={2014},
  publisher={Elsevier}
}
@article{osojnik2017isoup,
  title={Multi-label Classification via Multi-Target Regression on Data Streams},
  author={Osojnik, Alja{\v{z}} and Panov, Pan{\v{c}}e and D{\v{z}}eroski, Sa{\v{s}}o},
  journal={Machine Learning},
  volume={106},
  number={6},
  pages={745--770},
  year={2017},
  publisher={Springer}
}
@article{tai2012plst,
  title={Multilabel Classification with Principal Label Space Transformation},
  author={<NAME> and <NAME>},
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  number={9},
  pages={2508--2542},
  year={2012},
  publisher={MIT Press}
}
@article{furnkranz2008clr,
  title={Multilabel classification via calibrated label ranking},
  author={<NAME> and <NAME> and <NAME> and <NAME>},
  journal={Machine learning},
  volume={73},
  number={2},
  pages={133--153},
  year={2008},
  publisher={Springer}
}
@article{lewis2004rcv1,
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  pages={361--397},
  year={2004}
}
@inproceedings{trohidis2008music,
  title={Multi-Label Classification of Music into Emotions.},
  author={Trohidis, Konstantinos and Tsoumakas, <NAME> Kalliris, <NAME> Vlahavas, <NAME>},
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  year={2008}
}
@article{boutell2004scene,
  title={Learning Multi-Label Scene Classification},
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  publisher={Elsevier}
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@article{barutcuoglu2006hierarchical,
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@inproceedings{elisseeff2002kernel,
  title={A kernel method for multi-labelled classification},
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  year={2002}
}
@book{zhou2012ensemblebook,
  title={Ensemble methods: foundations and algorithms},
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}
@article{CACMStaff:2017:BD:3098997.3079064,
 author = {<NAME>},
 title = {Big Data},
 journal = {Commun. ACM},
 issue_date = {June 2017},
 volume = {60},
 number = {6},
 month = may,
 year = {2017},
 issn = {0001-0782},
 pages = {24--25},
 numpages = {2},
 acmid = {3079064},
 publisher = {ACM},
 address = {New York, NY, USA},
}  %url = {http://doi.acm.org/10.1145/3079064},
 %doi = {10.1145/3079064},
@article{gaber2005miningreview,
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}
@inproceedings{bifet2009adaptive-fourthings,
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}
@inproceedings{gama2009issues,
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}
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}
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}
@inproceedings{wang2017weighted,
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  organization={Springer}
}
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@inproceedings{zhu2005maxentropy-exactmatch,
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@inproceedings{domingos2000mining,
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}
@inproceedings{xioufis2011imbalance,
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  year={2011}
}
@inproceedings{bonab2016theoretical,
  title={A Theoretical Framework on the Ideal Number of Classifiers for Online Ensembles in Data Streams},
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}
@inproceedings{wang2003awe,
  title={Mining Concept-Drifting Data Streams using Ensemble Classifiers},
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  year={2003},
  organization={ACM}
}
@article{brzezinski2014aue2,
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  number={1},
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  year={2014},
  publisher={IEEE}
}
@inproceedings{bifet2007adwin,
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}
@article{wucrestani2015,
title = "A Geometric Framework for Data Fusion in Information Retrieval",
journal = "Information Systems",
volume = "50",
number = "Supplement C",
pages = "20 - 35",
year = "2015",
issn = "0306-4379",
author = "<NAME> and <NAME>",
keywords = "Database searching",
keywords = "Geometric modeling",
keywords = "Information retrieval",
keywords = "Data fusion"
}%doi = "https://doi.org/10.1016/j.is.2015.01.001",
%url = "http://www.sciencedirect.com/science/article/pii/S0306437915000113",
@article{bonab2018goowe,
  title={{GOOWE}: {G}eometrically {O}ptimum and {O}nline-{W}eighted {E}nsemble classifier for evolving data streams},
  author={<NAME> and <NAME>},
  journal={ACM Transactions on Knowledge Discovery from Data (TKDD)},
  volume={12},
  number={2},
  pages={25},
  year={2018},
  publisher={ACM}
}
@inproceedings{kuncheva2004classifier,
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}
@inproceedings{wang2012mining,
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}
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}
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}
@article{kolter2007dwm,
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