This paper is an overview of reconstructability analysis (RA), an approach to discrete multivariate modeling developed in the systems community. RA includes set-theoretic modeling of relations and information-theoretic modeling of frequency and probability distribution. It thus encompasses both statistical and nonstatisticalproblems. It overlaps with logic design and machine learning in engineering and with log-linear modeling in the social sciences. Its generality gives it considerable potential for knowledge representation and data mining.
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