Elements of information theory
Elements of information theory
BoosTexter: A Boosting-based Systemfor Text Categorization
Machine Learning - Special issue on information retrieval
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Knowledge Discovery in Multi-label Phenotype Data
PKDD '01 Proceedings of the 5th European Conference on Principles of Data Mining and Knowledge Discovery
Multi-labelled classification using maximum entropy method
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Collective multi-label classification
Proceedings of the 14th ACM international conference on Information and knowledge management
Multilabel Neural Networks with Applications to Functional Genomics and Text Categorization
IEEE Transactions on Knowledge and Data Engineering
ML-KNN: A lazy learning approach to multi-label learning
Pattern Recognition
Model-shared subspace boosting for multi-label classification
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Correlative multi-label video annotation
Proceedings of the 15th international conference on Multimedia
Extracting shared subspace for multi-label classification
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Multilabel classification via calibrated label ranking
Machine Learning
Random k-Labelsets: An Ensemble Method for Multilabel Classification
ECML '07 Proceedings of the 18th European conference on Machine Learning
Multi-label Classification Using Ensembles of Pruned Sets
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Learning multi-label alternating decision trees from texts and data
MLDM'03 Proceedings of the 3rd international conference on Machine learning and data mining in pattern recognition
Probabilistic Graphical Models: Principles and Techniques - Adaptive Computation and Machine Learning
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part III
Correlated multi-label feature selection
Proceedings of the 20th ACM international conference on Information and knowledge management
RW.KNN: a proposed random walk KNN algorithm for multi-label classification
Proceedings of the 4th workshop on Workshop for Ph.D. students in information & knowledge management
LIFT: multi-label learning with label-specific features
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Learning tree structure of label dependency for multi-label learning
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
Exploiting label dependency for hierarchical multi-label classification
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
Instance-Ranking: a new perspective to consider the instance dependency for classification
PAKDD'12 Proceedings of the 2012 Pacific-Asia conference on Emerging Trends in Knowledge Discovery and Data Mining
Exploiting label dependencies for improved sample complexity
Machine Learning
Tag recommendation in software information sites
Proceedings of the 10th Working Conference on Mining Software Repositories
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Multilabel relationship learning
ACM Transactions on Knowledge Discovery from Data (TKDD)
An efficient probabilistic framework for multi-dimensional classification
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
A feature-word-topic model for image annotation and retrieval
ACM Transactions on the Web (TWEB)
A study on multi-label classification
ICDM'13 Proceedings of the 13th international conference on Advances in Data Mining: applications and theoretical aspects
Multi-modal image annotation with multi-instance multi-label LDA
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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In multi-label learning, each training example is associated with a set of labels and the task is to predict the proper label set for the unseen example. Due to the tremendous (exponential) number of possible label sets, the task of learning from multi-label examples is rather challenging. Therefore, the key to successful multi-label learning is how to effectively exploit correlations between different labels to facilitate the learning process. In this paper, we propose to use a Bayesian network structure to efficiently encode the conditional dependencies of the labels as well as the feature set, with the feature set as the common parent of all labels. To make it practical, we give an approximate yet efficient procedure to find such a network structure. With the help of this network, multi-label learning is decomposed into a series of single-label classification problems, where a classifier is constructed for each label by incorporating its parental labels as additional features. Label sets of unseen examples are predicted recursively according to the label ordering given by the network. Extensive experiments on a broad range of data sets validate the effectiveness of our approach against other well-established methods.