Semantic Similarity in a Taxonomy by Refining the Relatedness of Concept Intended Senses

Authors

  • Anna Formica Istituto di Analisi dei Sistemi ed Informatica (IASI) "Antonio Ruberti", National Research Council, I-00185, Rome, Italy
  • Francesco Taglino Istituto di Analisi dei Sistemi ed Informatica (IASI) "Antonio Ruberti", National Research Council, I-00185, Rome, Italy

DOI:

https://doi.org/10.31577/cai_2023_1_191

Keywords:

Semantic similarity, information content, taxonomy, semantic relatedness, concept sense

Abstract

In this paper, we present an evolution of a novel approach for evaluating semantic similarity in a taxonomy, based on the well-known notion of information content. Such an approach takes into account not only the generic sense of a concept but also its intended sense in a given context. In this work semantic similarity is evaluated according to a refined relatedness measure between the generic sense and the intended sense of a concept, leading to higher correlation values with human judgment with respect to the original proposal.

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Published

2023-05-08

How to Cite

Formica, A., & Taglino, F. (2023). Semantic Similarity in a Taxonomy by Refining the Relatedness of Concept Intended Senses. Computing and Informatics, 42(1), 191–209. https://doi.org/10.31577/cai_2023_1_191