Which dissimilarity is to be used when extracting typologies in sequence analysis? A comparative study


Autoria(s): Massoni, Sebastien; Olteanu, Madalina; Villa-Vialaneix, Nathalie
Data(s)

2013

Resumo

Originally developed in bioinformatics, sequence analysis is being increasingly used in social sciences for the study of life-course processes. The methodology generally employed consists in computing dissimilarities between the trajectories and, if typologies are sought, in clustering the trajectories according to their similarities or dissemblances. The choice of an appropriate dissimilarity measure is a major issue when dealing with sequence analysis for life sequences. Several dissimilarities are available in the literature, but neither of them succeeds to become indisputable. In this paper, instead of deciding upon one dissimilarity measure, we propose to use an optimal convex combination of different dissimilarities. The optimality is automatically determined by the clustering procedure and is defined with respect to the within-class variance.

Identificador

http://eprints.qut.edu.au/61299/

Publicador

Springer

Relação

http://link.springer.com/content/pdf/10.1007%2F978-3-642-38679-4_5.pdf

Massoni, Sebastien, Olteanu, Madalina, & Villa-Vialaneix, Nathalie (2013) Which dissimilarity is to be used when extracting typologies in sequence analysis? A comparative study. Lecture Notes in Computer Science, 7902, pp. 69-79.

Fonte

QUT Business School; School of Economics & Finance

Tipo

Journal Article