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Title: Multi Label Classification: An Overview
Author(s): G. Tsoumakas, I. Katakis.
Availability: Click here to download the PDF (Acrobat Reader) file (17 pages).
Keywords: Multi-Label Classification, Classfication.
Appeared in: International Journal of Data Warehousing and Mining, David Taniar (Ed.), Idea Group Publishing, 3(3), pp. 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.
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131 Michael Stein, M. (2010) Automatic Detection of Multiple, Cascased Audio Effects in Guitar Recordings, Proc. of the 13th Int. Conference on Digital Audio Effects (DAFx-10), Graz, Austria , September 6-10, 2010
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157 Sanden, C., Zhang, J. (2011) An Empirical Study of Multi-Label Classifiers for Music Tag Annotation, Proc. 12th International Society for Music Information Retrieval Conference, ISMIR'11, October 24-28, pp. 717-722
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162 Ahmadi Abhari, K., Hamzeh, A., Hashemi, S. (2011) Voting based learning classifier system for multi-label classification, Genetic and Evolutionary Computation Conference, GECCO'11 - Companion Publication, pp. 355-359
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165 Pillai, I., Fumera, F., Roli, F. (2011) Classifier Selection Approaches for Multi-label Problems, Proc. 10th International Workshop on Multiple Classifier Systems, MCS 2011, Naples, Italy, June 15-17, pp. 167-176.
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179 Jiang, J.-Y., Lee, S.-J. (2011) FMLKNN: A fuzzy membership function based K-Nearest Neighbor approach for multi-label classification, ICIC Express Letters, 5 (4 A), pp. 1069-1075.
180 Vogrincic, S., Bosnic, Z. (2011) Ontology-based multi-label classification of economic articles, Computer Science and Information Systems, 8(1)
181 Alfaro, R., Allende, H. (2011) Text Representation in Multi-label Classification: Two New Input Representations, 10th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2011, Ljubljana, Slovenia, April 14-16, 2011, Proceedings, Part II, pp. 61-70.
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185 Vivian F. López Batista, Fernando Prieta Pintado, Ana Belén Gil, Sara Rodríguez and María N. Moreno (2011) A System for Multi-label Classification of Learning Objects, Proc. 6th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2011, pp. 523-531.
186 Guido Bologna, Anne-Lise Veuthey, Marco Pagni, Lydie Lane and Amos Bairoch (2011) A Preliminary Study on the Prediction of Human Protein Functions, Proceedings of the 4th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2011, La Palma, Canary Islands, Spain, May 30 - June 3, 2011.
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193 John Yearwood, Musa Mammadov and Dean Webb (2011) Profiling phishing activity based on hyperlinks extracted from phishing emails, Social Network Analysis and Mining, accepted.
194 Kanda1, J., Carvalho, A., Hruschka1, E., Soares, C. (2011) Selection of algorithms to solve traveling salesman problems using meta-learning, International Journal of Hybrid Intelligent Systems 8(3), pp. 117-128
195 Richards, J.W., Starr, D.L., Butler, N.R., Bloom, J.S., Brewer, J.M., Crellin-Quick, A., Higgins, J., Kennedy, R., Rischard, M. (2011) On machine-learned classification of variable stars with sparse and noisy time-series data (2011) Astrophysical Journal, 733 (1), art. no. 10.
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197 Pillai, I., Fumera, G., Roli, F. (2011) Classifier Selection Approaches for Multi-label Problems, Proc. 10th International Workshop on Multiple Classifier Systems, MCS 2011.
198 Ahmed, Z., Majeed, S. (2011) Machine Learning and Data Optimization using BPNN and GA in DOC, International Journal of Emerging Sciences, 1(2), 108-119, June 2011, ISSN: 2222-4254
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204 Feng, Y., Chen, Z. (2012) Multi-label software behavior learning, Proceedings - International Conference on Software Engineering, art. no. 6227093, pp. 1305-1308.
205 You, M., Liu, J., Li, G.-Z., Chen, Y. (2012) Embedded Feature Selection for Multi-label Classification of Music Emotions, International Journal of Computational Intelligence Systems, 5 (4), pp. 668-678.
206 Chen, Y., Lu, B.-L., Zhao, H. (2012) Parallel learning of large-scale multi-label classification problems with min-max modular LIBLINEAR, Proceedings of the International Joint Conference on Neural Networks, art. no. 6252679.
207 Verwaeren, J., Waegeman, W., De Baets, B. (2012) Learning partial ordinal class memberships with kernel-based proportional odds models, Computational Statistics and Data Analysis, 56 (4), pp. 928-942.
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209 Kumar,A.;Vembu,S.;Menon,A.;Elkan,C. (2012) Learning and Inference in Probabilistic Classifier Chains with Beam Search, Proceedings ECML PKDD 2012, pp. 665-680.
210 Dembczynski, K., Waegeman, W., Cheng, W., Hüllermeier, E. (2012) On label dependence and loss minimization in multi-label classification, Machine Learning, 88 (1-2), pp. 5-45.
211 Soylu,A.;Mödritscher,F.;Wild,F.;De Causmaecker,P.;Desmet,P. (2012) Mashups by Orchestration and Widget-based Personal Environments: Key Challenges, Solution Strategies, and an Application, Program: electronic library and information systems, Vol. 46 Iss: 4
212 Jing Zhang; Weiwei Hu; (2012) Effective multi-modal multi-label learning for automatic image annotation, Proceedings 9th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), pp.1216-1220, 29-31 May 2012
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214 Hariharan, B., Vishwanathan, S.V.N., Varma, M. (2012) Efficient max-margin multi-label classification with applications to zero-shot iearning, Machine Learning, 88 (1-2), pp. 127-155.
215 Read, J., Bifet, A., Holmes, G., Pfahringer, B. (2012) Scalable and efficient multi-label classification for evolving data streams, Machine Learning, 88 (1-2), pp. 243-272.
216 Wang,P.;Zhang,P.;Guo,L. (2012) Mining Multi-label Data Streams Using Ensemble-based Active Learning, In Proceedings of the 2012 SIAM International Conference on Data Mining (SDM-12), pp. 1131-1140, Anaheim, California, USA.
217 Henriques, R., Antunes, C. (2012) On the need of new approaches for the novel problem of long-term prediction over multi-dimensional data, Studies in Computational Intelligence, 429, pp. 121-138.
218 Rubin, T.N., Chambers, A., Smyth, P., Steyvers, M. (2012) Statistical topic models for multi-label document classification, Machine Learning, 88 (1-2), pp. 157-208.
219 Madjarov, G., Gjorgjevikj, D. (2012) Hybrid decision tree architecture utilizing local SVMs for multi-label classification, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7209 LNAI (PART 2), pp. 1-12.
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222 Gjorgji Madjarov, Dejan Gjorgjevikj, Sašo Džeroski (2012) Two stage architecture for multi-label learning, Pattern Recognition, Volume 45, Issue 3, March 2012, Pages 1019-1034, ISSN 0031-3203
223 Jiang, J.-Y., Tsai, S.-C., Lee, S.-J. (2012) FSKNN: Multi-label text categorization based on fuzzy similarity and k nearest neighbors, Expert Systems with Applications, 39 (3), pp. 2813-2821.
224 Hayat, M., Khan, A. (2012) MemHyb: Predicting membrane protein types by hybridizing SAAC and PSSM, Journal of Theoretical Biology, 292, pp. 93-102.
225 Xu, J. (2012) An efficient multi-label support vector machine with a zero label, Expert Systems with Applications, 39 (5), pp. 4796-4804.
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232 Steinberger, R., Ebrahim, M., Turchi, M. (2012) JRC EuroVoc Indexer JEX - A freely available multi-label categorisation tool. Proceedings of the 8th international conference on Language Resources and Evaluation (LREC'2012), Istanbul, 21-27 May 2012.
233 Xia, X., Yang, X., Li, S., Wu, C. (2012) A Bayesian Network nearest k-labels method for Multi-label classification, Advances in Information Sciences and Service Sciences, 4 (8), pp. 27-36.
234 Madjarov, G., Kocev, D., Gjorgjevikj, D., Džeroski, S. (2012) An extensive experimental comparison of methods for multi-label learning, Pattern Recognition, 45 (9), pp. 3084-3104.
235 Ortigosa-Hernández, J., Rodríguez, J.D., Alzate, L., Lucania, M., Inza, I., Lozano, J.A. (2012) Approaching Sentiment Analysis by using semi-supervised learning of multi-dimensional classifiers, Neurocomputing, 92, pp. 98-115.
236 Cebron, N., Richter, F., Lienhart, R. (2012) Decision tree induction from counterexamples, ICPRAM 2012 - Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods, 2, pp. 525-528.
237 He, J., Gu, H., Liu, W. (2012) Imbalanced multi-modal multi-label learning for subcellular localization prediction of human proteins with both single and multiple sites, PLoS ONE, 7 (6), art. no. e37155.
238 Zhang, J., Han, B., Wei, X., Tan, C., Chen, Y., Jiang, Y. (2012) A two-step target binding and selectivity support vector machines approach for virtual screening of dopamine receptor subtype-selective ligands, PLoS ONE, 7 (6), art. no. e39076.
239 Hayat, M., Khan, A., Yeasin, M. (2012) Prediction of membrane proteins using split amino acid and ensemble classification, Amino Acids, 42 (6), pp. 2447-2460.
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