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Advisor(s)
Abstract(s)
An important strategy for data classification consists in organising data
points in clusters. The k-means is a traditional optimisation method applied to
cluster data points. Using a labour market database, aiming the segmentation of this
market taking into account the heterogeneity resulting from different unemployment
characteristics observed along the Portuguese geographical space, we suggest the
application of an alternative method based on the computation of the dominant
eigenvalue of a matrix related with the distance among data points. This approach
presents results consistent with the results obtained by the k-means.
Description
Keywords
Portuguese
Citation
Balsa, Carlos; Nunes, Alcina; Barros, Elisa (2015). Optimization clustering techniques on register unemployment data. In Almeida, João Paulo; Oliveira, José F.; Pinto, Alberto A. (Eds.) Operational Research e 16th National Conference of the APDIO. p. 19-35. ISBN 978-3-319-20327-0
Publisher
Springer International Publishing