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Renato Cordeiro de Amorim
Renato Cordeiro de Amorim
Senior Lecturer in Computer Science and AI at the University of Essex
Verified email at essex.ac.uk - Homepage
Title
Cited by
Cited by
Year
Minkowski metric, feature weighting and anomalous cluster initializing in K-Means clustering
RC de Amorim, B Mirkin
Pattern Recognition 45 (3), 1061–1075, 2012
3892012
Recovering the number of clusters in data sets with noise features using feature rescaling factors
RC De Amorim, C Hennig
Information sciences 324, 126-145, 2015
3722015
Feature relevance in Ward’s hierarchical clustering using the Lp norm
R Cordeiro de Amorim
Journal of Classification 32 (1), 46-62, 2015
822015
A survey on feature weighting based K-Means algorithms
RC de Amorim
Journal of Classification 33 (2), 210-242, 2016
692016
Feature weighting as a tool for unsupervised feature selection
D Panday, RC de Amorim, P Lane
Information processing letters 129, 44-52, 2018
432018
Applying subclustering and L p distance in Weighted K-Means with distributed centroids
RC de Amorim, V Makarenkov
Neurocomputing 173 (3), 700--707, 2016
382016
Effective Spell Checking Methods Using Clustering Algorithms
RC de Amorim, M Zampieri
Recent Advances in Natural Language Processing, 172-178, 2013
362013
On Initializations for the Minkowski Weighted K-Means
RC de Amorim, P Komisarczuk
Lecture Notes in Computer Science, 45--55, 2012
352012
Constrained Clustering with Minkowski Weighted K-Means
RC de Amorim
Proceedings of the 13th IEEE International Symposium on Computational …, 2012
342012
Constrained Intelligent K-Means: Improving Results with Limited Previous Knowledge.
RC de Amorim
The Second International Conference on Advanced Engineering Computing and …, 2008
252008
A-Wardpβ: Effective hierarchical clustering using the Minkowski metric and a fast k-means initialisation
RC de Amorim, V Makarenkov, B Mirkin
Information Sciences 370, 343-354, 2016
232016
An Empirical Evaluation of Different Initializations on the Number of K-means Iterations
RC de Amorim
Lecture Notes in Computer Science 7629, 15-26, 2013
172013
Unsupervised feature selection for large data sets
RC de Amorim
Pattern Recognition Letters 128, 183-189, 2019
162019
The Minkowski central partition as a pointer to a suitable distance exponent and consensus partitioning
RC de Amorim, A Shestakov, B Mirkin, V Makarenkov
Pattern Recognition 67, 62-72, 2017
152017
Between Sound and Spelling: Combining Phonetics and Clustering Algorithms to Improve Target Word Recovery
M Zampieri, RC de Amorim
Proceedings of the 9th International Conference on Natural Language Processing, 2014
142014
On partitional clustering of malware
RC de Amorim, P Komisarczuk
The First International Workshop on Cyber Patterns: Unifying Design Patterns …, 2012
13*2012
Weighting features for Partition Around Medoids using the Minkowski metric
RC de Amorim, T Fenner
Lecture Notes in Computer Science, 35--44, 2012
132012
Learning feature weights for K-Means clustering using the Minkowski metric
RC de Amorim
Birkbeck, University of London, 2011
112011
Computational Methods of Feature Selection, Huan Liu, Hiroshi Motoda, CRC Press, Boca Raton, FL (2007). 440 pp., Price: $93.95, ISBN: 978-1-58488-878-9
RC de Amorim
Information Processing & Management 45 (4), 490-493, 2009
112009
Challenges in developing Capture-HPC exclusion lists
M Puttaroo, P Komisarczuk, RC de Amorim
Proceedings of the 7th International Conference on Security of Information …, 2014
92014
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