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In vivo evaluation of the brain white matter maturation is still a challenging task with no existing gold standards. In this article we propose an original approach to evaluate the early maturation of the white matter bundles, which is based on comparison of infant and adult groups using the Mahalanobis distance computed from four complementary MRI(More)
Nowadays data sets are available in very complex and heterogeneous ways. The mining of such data collections is essential to support many real-world applications ranging from healthcare to marketing. In this work, we focus on the analysis of " complex " sequential data by means of interesting sequential patterns. We approach the problem using an elegant(More)
In this paper, we are interested in the analysis of sequential data and we propose an original framework based on FCA. For that, we introduce sequential pattern structures, an original specification of pattern structures for dealing with sequential data. Sequential pattern structures are given by a subsumption operation between set of sequences, based on(More)
Classification is an important task in data analysis and learning. Classification can be performed using supervised or unsupervised methods. From the unsupervised point of view, Formal Concept Analysis (FCA) can be used for such a task in an efficient and well-founded way. From the supervised point of view, emerging patterns rely on pattern mining and can(More)
Nowadays data sets are available in very complex and heterogeneous ways. Mining of such data collections is essential to support many real-world applications ranging from healthcare to marketing. In this work, we focus on the analysis of " complex " sequential data by means of interesting sequential patterns. We approach the problem using the elegant(More)
A new general and efficient architecture for working with pattern structures, an extension of FCA for dealing with " complex " descriptions , is introduced and implemented in a subsystem of Formal Concept Analysis Research Toolbox (FCART). The architecture is universal in terms of possible dataset structures and formats, techniques of pattern structure(More)
Formal concept analysis (FCA) is a well-founded method for data analysis and has many applications in data mining. Pattern structures is an extension of FCA for dealing with complex data such as sequences or graphs. However the computational complexity of computing with pattern structures is high and projections of pattern structures were introduced for(More)
In this paper, we revisit an original proposition on pattern structures for structured sets of attributes. There are several reasons for carrying out this kind of research work. The original proposition does not give many details on the whole framework, and especially on the possible ways of implementing the similarity operation. There exists an alternative(More)