Reference : Direct clustering of a two-mode binary data-matrix
Scientific journals : Article
Social & behavioral sciences, psychology : Multidisciplinary, general & others
Direct clustering of a two-mode binary data-matrix
Krolak-Schwerdt, Sabine mailto [University of Luxembourg > Faculty of Language and Literature, Humanities, Arts and Education (FLSHASE) > Languages, Culture, Media and Identities (LCMI) >]
Orlik, Peter [> >]
Universität des Saarlandes: Arbeiten der Fachrichtung Psychologie
[en] In this paper a discrete, categorical model is proposed for two-:­
mode data matrices with binary entries Xij E {0, 1}. The method operates
directly upon a raw input (objects by attributes) data array by determining
two-mode submatrices whose entries entirely have values x;j = 1. In
addition, different submatrices are required to have a minimum set of objectattribute-
pairs in common. Objects and attributes are classified simultaneously
in a number ofjoint clusters. The method may be characterized as a
non-hierarchical clustering procedure and in its model function to predict the
data it is similar to Boolean factor analy􀢛is. Basically, the proposed method
dubbed ' GRIDPAT' (for 'PATtern analysis of GRIDs') was developped for the
structural representation of self concept data. Its relations to basic notions
of Formal Concept Analysis and blockmodeling are discussed. An illustrative
application of the approach is provided.

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