Paper Info
Title
Which dissimilarity is to be used when extracting typologies in sequence analysis? a comparative study
Abstract
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.
Year
DOI
Venue
2013
10.1007/978-3-642-38679-4_5
IWANN (1)
Keywords
Field
DocType
appropriate dissimilarity measure,comparative study,dissimilarity measure,life-course process,life sequence,social science,major issue,sequence analysis,optimal convex combination,clustering procedure,different dissimilarity
Data mining,Convex combination,Artificial intelligence,Cluster analysis,Mathematics,Machine learning,Sequence analysis
Conference
Volume
ISSN
Citations 
7902
0302-9743
0
PageRank 
References 
Authors
0.34
5
3
Name
Order
Citations
PageRank
Sébastien Massoni130.76
Madalina Olteanu26810.50
Nathalie Villa-Vialaneix37210.94