Detecção de anomalias (Portuguese Wikipedia)
Analysis of information sources in references of the Wikipedia article "Detecção de anomalias" in Portuguese language version.
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computer.org
- Liu, Fei Tony; Ting, Kai Ming; Zhou, Zhi-Hua (dezembro de 2008). Isolation Forest. [S.l.: s.n.] ISBN 9780769535029. doi:10.1109/ICDM.2008.17
doi.org
dx.doi.org
- Zimek, Arthur; Schubert, Erich (2017), «Outlier Detection», ISBN 9781489979933, Springer New York, Encyclopedia of Database Systems: 1–5, doi:10.1007/978-1-4899-7993-3_80719-1
- «A Survey of Outlier Detection Methodologies» (PDF). Artificial Intelligence Review. 22. CiteSeerX 10.1.1.318.4023
. doi:10.1007/s10462-004-4304-y - «Anomaly detection: A survey». ACM Computing Surveys. 41. doi:10.1145/1541880.1541882
- «An Experiment with the Edited Nearest-Neighbor Rule». IEEE Transactions on Systems, Man, and Cybernetics. 6. doi:10.1109/TSMC.1976.4309523
- Smith, M. R.; Martinez, T. «Improving classification accuracy by identifying and removing instances that should be misclassified». The 2011 International Joint Conference on Neural Networks. [S.l.: s.n.] ISBN 978-1-4244-9635-8. doi:10.1109/IJCNN.2011.6033571
- «There and back again: Outlier detection between statistical reasoning and data mining algorithms». Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. 8. ISSN 1942-4787. doi:10.1002/widm.1280
- «Distance-based outliers: Algorithms and applications». The VLDB Journal the International Journal on Very Large Data Bases. 8. CiteSeerX 10.1.1.43.1842. doi:10.1007/s007780050006
- Liu, Fei Tony; Ting, Kai Ming; Zhou, Zhi-Hua (dezembro de 2008). Isolation Forest. [S.l.: s.n.] ISBN 9780769535029. doi:10.1109/ICDM.2008.17
- «Local outlier detection reconsidered: A generalized view on locality with applications to spatial, video, and network outlier detection». Data Mining and Knowledge Discovery. 28. doi:10.1007/s10618-012-0300-z
- «Tensor-based anomaly detection: An interdisciplinary survey». Knowledge-Based Systems. 98. doi:10.1016/j.knosys.2016.01.027
- «A survey on unsupervised outlier detection in high-dimensional numerical data». Statistical Analysis and Data Mining. 5. doi:10.1002/sam.11161
- «Estimating the Support of a High-Dimensional Distribution». Neural Computation. 13. CiteSeerX 10.1.1.4.4106. PMID 11440593. doi:10.1162/089976601750264965
- Hawkins, Simon; He, Hongxing; Williams, Graham; Baxter, Rohan. «Outlier Detection Using Replicator Neural Networks». Data Warehousing and Knowledge Discovery. Col: Lecture Notes in Computer Science. 2454. [S.l.: s.n.] ISBN 978-3-540-44123-6. doi:10.1007/3-540-46145-0_17
- «Discovering cluster-based local outliers». Pattern Recognition Letters. 24. CiteSeerX 10.1.1.20.4242. doi:10.1016/S0167-8655(03)00003-5
- «Hierarchical Density Estimates for Data Clustering, Visualization, and Outlier Detection». ACM Transactions on Knowledge Discovery from Data. 10. doi:10.1145/2733381
- Lazarevic, A.; Kumar, V. Feature bagging for outlier detection. [S.l.: s.n.] ISBN 978-1-59593-135-1. doi:10.1145/1081870.1081891
- «Ensembles for unsupervised outlier detection». ACM SIGKDD Explorations Newsletter. 15. doi:10.1145/2594473.2594476
- «On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study». Data Mining and Knowledge Discovery. 30. ISSN 1384-5810. doi:10.1007/s10618-015-0444-8
- «An Intrusion-Detection Model» (PDF). IEEE Transactions on Software Engineering. SE-13. CiteSeerX 10.1.1.102.5127. doi:10.1109/TSE.1987.232894
- Teng, H. S.; Chen, K.; Lu, S. C. Adaptive real-time anomaly detection using inductively generated sequential patterns (PDF). [S.l.: s.n.] ISBN 978-0-8186-2060-7. doi:10.1109/RISP.1990.63857
dtic.mil
lmu.de
dbs.ifi.lmu.de
nih.gov
ncbi.nlm.nih.gov
- «Estimating the Support of a High-Dimensional Distribution». Neural Computation. 13. CiteSeerX 10.1.1.4.4106. PMID 11440593. doi:10.1162/089976601750264965
psu.edu
citeseerx.ist.psu.edu
- «A Survey of Outlier Detection Methodologies» (PDF). Artificial Intelligence Review. 22. CiteSeerX 10.1.1.318.4023. doi:10.1007/s10462-004-4304-y
- «Distance-based outliers: Algorithms and applications». The VLDB Journal the International Journal on Very Large Data Bases. 8. CiteSeerX 10.1.1.43.1842. doi:10.1007/s007780050006
- «Estimating the Support of a High-Dimensional Distribution». Neural Computation. 13. CiteSeerX 10.1.1.4.4106. PMID 11440593. doi:10.1162/089976601750264965
- «Discovering cluster-based local outliers». Pattern Recognition Letters. 24. CiteSeerX 10.1.1.20.4242. doi:10.1016/S0167-8655(03)00003-5
- «An Intrusion-Detection Model» (PDF). IEEE Transactions on Software Engineering. SE-13. CiteSeerX 10.1.1.102.5127. doi:10.1109/TSE.1987.232894
- «Computer System Intrusion Detection: A Survey». Technical Report, Department of Computer Science, University of Virginia, Charlottesville, VA. CiteSeerX 10.1.1.24.7802
umbc.edu
csee.umbc.edu
- «Data mining for network intrusion detection» (PDF). Proceedings NSF Workshop on Next Generation Data Mining
unc.edu
cs.unc.edu
- Teng, H. S.; Chen, K.; Lu, S. C. Adaptive real-time anomaly detection using inductively generated sequential patterns (PDF). [S.l.: s.n.] ISBN 978-0-8186-2060-7. doi:10.1109/RISP.1990.63857
usp.br
lapad-web.icmc.usp.br
whiterose.ac.uk
eprints.whiterose.ac.uk
- «A Survey of Outlier Detection Methodologies» (PDF). Artificial Intelligence Review. 22. CiteSeerX 10.1.1.318.4023. doi:10.1007/s10462-004-4304-y
worldcat.org
- «There and back again: Outlier detection between statistical reasoning and data mining algorithms». Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. 8. ISSN 1942-4787. doi:10.1002/widm.1280
- «On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study». Data Mining and Knowledge Discovery. 30. ISSN 1384-5810. doi:10.1007/s10618-015-0444-8