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Cited by 26 publications
(21 citation statements)
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References 13 publications
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“…However, several initiatives have proposed theoretical tools to ease the characterisation of measures, for instance by means of measure unification (Cross et al, 2013;Cross, 2006;Cross and Yu, 2010;Pirró and Euzenat, 2010a;Mazandu and Mulder, 2013;Cross et al, 2013;Harispe et al, 2013c), and by means of semantic model unification in distributional semantics, e.g. (Baroni and Lenci, 2010).…”
Section: Develop Theoretical Toolsmentioning
confidence: 99%
“…However, several initiatives have proposed theoretical tools to ease the characterisation of measures, for instance by means of measure unification (Cross et al, 2013;Cross, 2006;Cross and Yu, 2010;Pirró and Euzenat, 2010a;Mazandu and Mulder, 2013;Cross et al, 2013;Harispe et al, 2013c), and by means of semantic model unification in distributional semantics, e.g. (Baroni and Lenci, 2010).…”
Section: Develop Theoretical Toolsmentioning
confidence: 99%
“…Finally, the interest similarity between users x and y integrates syntactic and semantic similarities. It is calculated as a linear combination of two measures: cosine similarity and ontological similarity of the users interest lists. Syntactic similarity accounts for the co‐occurrence of terms only, with no consideration of synonyms (different words with same meaning).…”
Section: The Proposed Users Similarity Measurementioning
confidence: 99%
“…1 It calculates the percentage of cases where at least one neighbor has rated a service not rated by active user. Larger coverage value indicates better prediction, and it is calculated using Equation 21:…”
Section: Evaluation Metricsmentioning
confidence: 99%
“…Various definitions for (dis)similarity have been proposed in the literature in various data domains [3], [4], [25] without consensus. Motivated by a popular definition of similarity between fuzzy sets [25], we propose the following definition in a mathematical lattice.…”
Section: Similarity Measures On Latticesmentioning
confidence: 99%
“…Another approach for dealing with nonnumerical data is by developing domain-specific (mathematical) tools. Drawbacks of the latter approach include: first, different mathematical tools need to be "ad-hoc" devised in different (nonnumerical) data domains and, second, performance cannot, often, be tuned [3], [4]. Yet another approach has been proposed lately based on mathematical lattice theory as explained next.…”
Section: Introductionmentioning
confidence: 99%