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Semantic Similarity Based on Taxonomies

Articolo
Data di Pubblicazione:
2023
Abstract:
The evaluation of the semantic similarity of concepts organized according to taxonomies is a long-standing problem in computer science and has attracted great attention from researchers over the decades. In this regard, the notion of information content plays a key role, and semantic similarity measures based on it are still on the rise. In this review, we address the methods for evaluating the semantic similarity between either concepts or sets of concepts belonging to a taxonomy that, often, in the literature, adopt different notations and formalisms. The results of this systematic literature review provide researchers and academics with insight into the notions that the methods discussed have in common through the use of the same notation, as well as their differences, overlaps, and dependencies, and, in particular, the role of the notion of information content in the evaluation of semantic similarity. Furthermore, in this review, a comparative analysis of the methods for evaluating the semantic similarity between sets of concepts is provided.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
semantic similarity; knowledge-based methods; taxonomy; information content
Elenco autori:
Formica, Anna; Taglino, Francesco; Mele, Ida
Autori di Ateneo:
FORMICA ANNA
MELE IDA
TAGLINO FRANCESCO
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/450943
Pubblicato in:
APPLIED SCIENCES
Journal
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