The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Selecting informative features with fuzzy-rough sets and its application for complex systems monitoring
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Citations
Cites
A Global Geometric Framework for Nonlinear Dimensionality Reduction
Tenenbaum, J. B., Silva, V. D., & Langford, J. C. (2000) · Science · doi:10.1126/science.290.5500.2319 · Cited by 13,585
Cited by
Neighborhood rough set based heterogeneous feature subset selection
Hu, Q., Yu, D., Liu, J., & Wu, C. (2008) · Information Sciences · doi:10.1016/j.ins.2008.05.024 · Cited by 1,085
Semantics-preserving dimensionality reduction: rough and fuzzy-rough-based approaches
Jensen, R., & Shen, Q. (2004) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2004.96 · Cited by 667
Self-citationInformation-preserving hybrid data reduction based on fuzzy-rough techniques
Hu, Q., Yu, D., & Xie, Z. (2006) · Pattern Recognition Letters · doi:10.1016/j.patrec.2005.09.004 · Cited by 462
Methodology for long-term prediction of time series
Sorjamaa, A., Hao, J., Reyhani, N., Ji, Y., & Lendasse, A. (2007) · Neurocomputing · doi:10.1016/j.neucom.2006.06.015 · Cited by 438
Metadata
- Authors
- Shen, Q., & Jensen, R.
- Venue
- Pattern Recognition
- Publisher
- Elsevier BV
- Published
- 2004-07
- Volume
- 37
- Issue
- 7
- Pages
- 1351-1363
- ISSN
- 0031-3203 (ISSN-L)
- OpenAlex
- W2108268240
- Cited by
- 221
- References
- 1
- FWCI
- 12.24
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
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- CoChat. (2026). Citation check: Selecting informative features with fuzzy-rough sets and its application for complex systems monitoring. https://app.cochat.ai/papers/10.1016/j.patcog.2003.10.016
- The paper
- Shen, Q., & Jensen, R. (2004). Selecting informative features with fuzzy-rough sets and its application for complex systems monitoring. Pattern Recognition. https://doi.org/10.1016/j.patcog.2003.10.016
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.
