A parametric similarity method: Comparative experiments based on semantically annotated large datasets

Nicola, Antonio De; Formica, Anna; Missikoff, Michele; Pourabbas, Elaheh; Taglino, Francesco

doi:10.1016/j.websem.2023.100773

Cited by 5 publications

(32 citation statements)

References 51 publications

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“…Our latest experimentation, which is shown in Section 6, confirms the results of the comparative assessment presented in [18], i.e., SemSim p , which, when configured according to a specific selection of parameters, improves the performance of the four methods mentioned above. For this reason, it is recalled in the next section in detail.…”

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confidence: 75%

“…This is an extensional, or corpus-based, method as the likelihood of a concept is computed as the relative frequency of that concept in a corpus of documents. Another extensional method is annotation frequency IC [18], which exploits the inverse document frequency (IDF) of a concept in a corpus of textual resources [19]. In particular, in [18], this method is applied to annotation vectors, i.e., sets of concepts of a taxonomy that are used to semantically annotate digital resources.…”

Section: Methods For Computing the Information Content Of A Concept I...mentioning

confidence: 99%

“…Another extensional method is annotation frequency IC [18], which exploits the inverse document frequency (IDF) of a concept in a corpus of textual resources [19]. In particular, in [18], this method is applied to annotation vectors, i.e., sets of concepts of a taxonomy that are used to semantically annotate digital resources.…”

Section: Methods For Computing the Information Content Of A Concept I...mentioning

confidence: 99%

“…However, these are set-theoretic methods that are not addressed in this review as they do not rely on a given taxonomy of concepts. With regard to the taxonomy-based similarity measures, in this section, we recall five methods: the WNSim similarity [53], the measures introduced by Rezaei and Fränti [46], Haase et al [54], and Wang et al [55], and the SemSim p similarity [18].…”

Section: Methods For Computing Semantic Similarity Between Sets Of Co...mentioning

confidence: 99%

“…where the IC is computed according to the Resnik IC (see Section 2). • SemSim p similarity [18] is derived from the SemSim method [27], which has been conceived for evaluating the semantic similarity of resources (i.e., real-world entities) annotated by sets of concepts taken from a taxonomy. It is a parametric measure depending on a weight associated with the concepts of the taxonomy, and a normalization factor is used when the two compared annotation vectors have different cardinalities.…”

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confidence: 99%

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Semantic Similarity Based on Taxonomies

De Nicola,

Formica,

Mele

et al. 2023

Applied Sciences

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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.

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confidence: 75%