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The aim of this paper is to compare two kinds of features in topic-based clustering of some literary poems by the Romanian poet, Mihai Eminescu. Using Precision, Recall, Rand Index, Relative Precision and Purity measures for evaluating the clustering results, we conclude that the topics of poems are better characterized by the phonemes as features than by some geometric properties (described by the indicators: V/N; A; Λ; Var(Λ); Gini; Var(Gini), of the rank-frequency sequence of word forms.

Topic-based clustering of poems using phonemes versus geometric properties