The DOI matches its Crossref record; 82 of the 82 references it cites were found in a registry or an index.
Label ranking by learning pairwise preferences
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Citations
Cites
(2005) · Statistics for Biology and Health · doi:10.1007/0-387-27255-0_9 · Cited by 20,133
UCI Repository of machine learning databases
Blake, C. L. (1998) · Medical Entomology and Zoology · Cited by 10,582
Witten, I. H. (2008) · Cited by 9,143
The proof and measurement of association between two things
Spearman, C. (1904) · The American Journal of Psychology · doi:10.2307/1412159 · Cited by 8,039
Lecture Notes in Artificial Intelligence
Brézillon, P., & Bouquet, P. (1999) · Cited by 7,473
A comparison of methods for multiclass support vector machines
Hsu, C.-W., & Lin, C.-J. (2002) · IEEE Transactions on Neural Networks · doi:10.1109/72.991427 · Cited by 6,838
Kendall, M. G. (1957) · Biometrika · doi:10.2307/2333282 · Cited by 6,383
Advances in kernel methods: support vector learning
Schölkopf, B., Burges, C. J. C., & Smola, A. J. (1999) · doi:10.5555/299094 · Cited by 5,789
Data mining: practical machine learning tools and techniques with Java implementations
Witten, I. H., & Frank, E. (2002) · ACM SIGMOD Record · doi:10.1145/507338.507355 · Cited by 5,137
Probabilistic Outputs for Support vector Machines and Comparisons to Regularized Likelihood Methods
Platt, J. C. (1999) · Cited by 4,827
Cited by
Multilabel classification via calibrated label ranking
Fürnkranz, J., Hüllermeier, E., Loza Mencía, E., & Brinker, K. (2008) · Machine Learning · doi:10.1007/s10994-008-5064-8 · Cited by 909
Self-citationRandom k-Labelsets for Multilabel Classification
Tsoumakas, G., Katakis, I., & Vlahavas, I. (2011) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2010.164 · Cited by 895
Lift: Multi-Label Learning with Label-Specific Features
Zhang, M.-L., & Wu, L. (2015) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2014.2339815 · Cited by 536
A Tutorial on Multilabel Learning
Gibaja, E., & Ventura, S. (2015) · ACM Computing Surveys · doi:10.1145/2716262 · Cited by 527
Addressing imbalance in multilabel classification: Measures and random resampling algorithms
Charte, F., Rivera, A. J., del Jesus, M. J., & Herrera, F. (2015) · Neurocomputing · doi:10.1016/j.neucom.2014.08.091 · Cited by 288
Metadata
- Authors
- Hüllermeier, E., Fürnkranz, J., Cheng, W., & Brinker, K.
- Venue
- Artificial Intelligence
- Publisher
- Elsevier BV
- Published
- 2008-11
- Volume
- 172
- Issue
- 16-17
- Pages
- 1897-1916
- ISSN
- 0004-3702 (ISSN-L)
- OpenAlex
- W2102705755
- Cited by
- 536
- References
- 82
- FWCI
- 39.22
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
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- CoChat. (2026). Citation check: Label ranking by learning pairwise preferences. https://app.cochat.ai/papers/10.1016/j.artint.2008.08.002
- The paper
- Hüllermeier, E., Fürnkranz, J., Cheng, W., & Brinker, K. (2008). Label ranking by learning pairwise preferences. Artificial Intelligence. https://doi.org/10.1016/j.artint.2008.08.002
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
