Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Pairwise classification and support vector machines
Advances in kernel methods
Classification by pairwise coupling
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Improved Boosting Algorithms Using Confidence-rated Predictions
Machine Learning - The Eleventh Annual Conference on computational Learning Theory
BoosTexter: A Boosting-based Systemfor Text Categorization
Machine Learning - Special issue on information retrieval
An Evaluation of Statistical Approaches to Text Categorization
Information Retrieval
The Journal of Machine Learning Research
A family of additive online algorithms for category ranking
The Journal of Machine Learning Research
A survey of kernels for structured data
ACM SIGKDD Explorations Newsletter
RCV1: A New Benchmark Collection for Text Categorization Research
The Journal of Machine Learning Research
Support vector machine learning for interdependent and structured output spaces
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Hierarchical document categorization with support vector machines
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
Efficient Learning of Label Ranking by Soft Projections onto Polyhedra
The Journal of Machine Learning Research
Kernel-Based Learning of Hierarchical Multilabel Classification Models
The Journal of Machine Learning Research
Multiple Graph Alignment for the Structural Analysis of Protein Active Sites
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Speaker identification via support vector classifiers
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01
Intelligent Data Analysis
Label ranking by learning pairwise preferences
Artificial Intelligence
Efficient Pairwise Classification
ECML '07 Proceedings of the 18th European conference on Machine Learning
A Unified Model for Multilabel Classification and Ranking
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
IEEE Transactions on Neural Networks
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
Efficient Pairwise Multilabel Classification for Large-Scale Problems in the Legal Domain
ECML PKDD '08 Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II
Classifier Chains for Multi-label Classification
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
Representing uncertainty on set-valued variables using belief functions
Artificial Intelligence
Multi-label learning by exploiting label dependency
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Mr.KNN: soft relevance for multi-label classification
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Evidential multi-label classification approach to learning from data with imprecise labels
IPMU'10 Proceedings of the Computational intelligence for knowledge-based systems design, and 13th international conference on Information processing and management of uncertainty
Image to text translation by multi-label classification
ICIC'10 Proceedings of the Advanced intelligent computing theories and applications, and 6th international conference on Intelligent computing
On exploiting hierarchical label structure with pairwise classifiers
ACM SIGKDD Explorations Newsletter
Dual layer voting method for efficient multi-label classification
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Multi-label learning approaches for music instrument recognition
ISMIS'11 Proceedings of the 19th international conference on Foundations of intelligent systems
Aggregating independent and dependent models to learn multi-label classifiers
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part II
On the stratification of multi-label data
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part III
Learning from label preferences
DS'11 Proceedings of the 14th international conference on Discovery science
Two stage architecture for multi-label learning
Pattern Recognition
Using random walks for multi-label classification
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
An efficient multi-label support vector machine with a zero label
Expert Systems with Applications: An International Journal
Multilabel classification using heterogeneous ensemble of multi-label classifiers
Pattern Recognition Letters
Efficient multilabel classification algorithms for large-scale problems in the legal domain
Semantic Processing of Legal Texts
Improving multilabel classification performance by using ensemble of multi-label classifiers
MCS'10 Proceedings of the 9th international conference on Multiple Classifier Systems
Multi-label classification using boolean matrix decomposition
Proceedings of the 27th Annual ACM Symposium on Applied Computing
LIFT: multi-label learning with label-specific features
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
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
Multilabel classification with principal label space transformation
Neural Computation
Multi-label ensemble based on variable pairwise constraint projection
Information Sciences: an International Journal
Fast multi-label core vector machine
Pattern Recognition
Semi-supervised multi-label classification: a simultaneous large-margin, subspace learning approach
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part II
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part III
Multi-label lego -- enhancing multi-label classifiers with local patterns
IDA'12 Proceedings of the 11th international conference on Advances in Intelligent Data Analysis
Iterative classification for multiple target attributes
Journal of Intelligent Information Systems
Relational large scale multi-label classification method for video categorization
Multimedia Tools and Applications
Multilabel relationship learning
ACM Transactions on Knowledge Discovery from Data (TKDD)
Neighborhood rough sets based multi-label classification for automatic image annotation
International Journal of Approximate Reasoning
Probabilistic multi-label classification with sparse feature learning
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Dependent binary relevance models for multi-label classification
Pattern Recognition
| Hi-index | 0.00 |
Label ranking studies the problem of learning a mapping from instances to rankings over a predefined set of labels. Hitherto existing approaches to label ranking implicitly operate on an underlying (utility) scale which is not calibrated in the sense that it lacks a natural zero point. We propose a suitable extension of label ranking that incorporates the calibrated scenario and substantially extends the expressive power of these approaches. In particular, our extension suggests a conceptually novel technique for extending the common learning by pairwise comparison approach to the multilabel scenario, a setting previously not being amenable to the pairwise decomposition technique. The key idea of the approach is to introduce an artificial calibration label that, in each example, separates the relevant from the irrelevant labels. We show that this technique can be viewed as a combination of pairwise preference learning and the conventional relevance classification technique, where a separate classifier is trained to predict whether a label is relevant or not. Empirical results in the area of text categorization, image classification and gene analysis underscore the merits of the calibrated model in comparison to state-of-the-art multilabel learning methods.