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Neutrosophic Refined Similarity Measure Based on Cosine Function [PDF]
Neutrosophic Sets and Systems, 2014 In this paper, the cosine similarity measure of neutrosophic refined (multi-) sets is proposed and its properties are studied. The concept of this cosine similarity measure of neutrosophic refined sets is the extension of improved cosine similarity ...
Said Broumi, Florentin Smarandache
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, 2018 This is a tutorial on the cosine similarity measure. Its meaning in the context of uncorrelated and orthogonal variables is examined.
Edel Garcia (5460320)
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Cosine Similarity Measure of Interval Valued Neutrosophic Sets [PDF]
Neutrosophic Sets and Systems, 2014 In this paper, we define a new cosine similarity between two interval valued neutrosophic sets based on Bhattacharya’s distance [19]. The notions of interval valued neutrosophic sets (IVNS, for short) will be used as vector representations in 3D-vector ...
Said Broumi, Florentin Smarandache
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On the distribution of cosine similarity with application to biology [PDF]
, 2023 Cosine similarity is an established similarity metric for computing associations on vectors, and it is commonly used to identify related samples from biological perturbational data. The distribution of cosine similarity changes with the covariance of the data, and this in turn affects the statistical power to identify related signals.
Smith, Ian +4 more
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Cosine Similarity Measure Based Multi-attribute Decision-making with Trapezoidal Fuzzy Neutrosophic Numbers [PDF]
Neutrosophic Sets and Systems, 2015 The objective of the study is to present cosine similarity measure based multi-attribute decision making under neutrosophic environment. The assesments of alternatives over the attributes are expressed with trapezoidal fuzzy neutrosophic numbers in which
Pranab Biswas +2 more
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Exploring the Sharpened Cosine Similarity
CoRR, 2023 Accepted to I Can't Believe It's Not Better Workshop (ICBINB) at NeurIPS ...
Skyler Wu +3 more
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A Quantum Binary Classifier based on Cosine Similarity [PDF]
2021 IEEE International Conference on Quantum Computing and Engineering (QCE), 2021 We introduce the quantum implementation of a binary classifier based on cosine similarity between data vectors. The proposed quantum algorithm evaluates the classifier on a set of data vectors with time complexity that is logarithmic in the product of the set cardinality and the dimension of the vectors. It is based just on a suitable state preparation
Pastorello, Davide, Blanzieri, Enrico
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A Triangle Inequality for Cosine Similarity [PDF]
, 2021 Similarity search is a fundamental problem for many data analysis techniques. Many efficient search techniques rely on the triangle inequality of metrics, which allows pruning parts of the search space based on transitive bounds on distances. Recently, Cosine similarity has become a popular alternative choice to the standard Euclidean metric, in ...
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Complexity, 2018 We propose the cosine similarity measures for intuitionistic fuzzy linguistic sets (IFLSs) and interval-valued intuitionistic fuzzy linguistic sets (IVIFLSs), which are expressed by the linguistic scale function based on the cosine function.
Donghai Liu, Xiaohong Chen, Dan Peng
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