Authors: | Randel, Rodrigo Aloise, Daniel Mladenović, Nenad Hansen, Pierre |
Title: | On the k-Medoids Model for Semi-supervised Clustering |
Journal: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Volume: | 11328 LNCS |
First page: | 13 |
Last page: | 27 |
Conference: | 6th International Conference on Variable Neighborhood Search, ICVNS 2018; Sithonia; Greece; 4 October 2018 through 7 October 2018 |
Issue Date: | 1-Jan-2019 |
Rank: | M33 |
ISBN: | 978-3-030-15842-2 |
ISSN: | 0302-9743 |
DOI: | 10.1007/978-3-030-15843-9_2 |
Abstract: | Clustering is an automated and powerful technique for data analysis. It aims to divide a given set of data points into clusters which are homogeneous and/or well separated. A major challenge with clustering is to define an appropriate clustering criterion that can express a good separation of data into homogeneous groups such that the obtained clustering solution is meaningful and useful to the us... |
Keywords: | k-medoids | Semi-supervised clustering | Variable Neighborhood Search |
Publisher: | Springer Link |
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