Modeling a most specific generalization in domain taxonomies

Hayrapetyan, Z. and Mirkin, Boris and Nascimento, S. and Fenner, Trevor and Frolov, D. (2023) Modeling a most specific generalization in domain taxonomies. In: 17th Conference of the International Federation of Classification Societies (IFCS 2022), 19-23 July 2022, Porto, Portugal. (In Press)

Abstract

We define a most specific generalization of a fuzzy set of topics assigned to leaves of the rooted tree of a domain taxonomy. This generalization lifts the set to its “head subject” node in the higher ranks of the taxonomy tree. The head subject is supposed to “tightly” cover the query set, possibly involving some errors referred to as “gaps” and “offshoots”. We develop a method to globally maximize either the parsimony or the likelihood of a scenario involving gains and losses of the general concept manifested in a fuzzy cluster of leaf nodes of the taxonomy. Supplemented with fuzzy c-means clustering, this allows us to obtain meaningful generalizations for fuzzy thematic clusters of Data Science topics using several dozen thousand abstracts from issues of relevant research journals published from 2000 on.

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