Add to ORKGSimilarity and dissimilarity are rarely formalized concepts in Artificial Intelligence (AI). Similarity and dissimilarity have a psychological origin, and they have been adapted to AI. In this field, however, similarity and dissimilarity choice is not always dependent on the problem to solve. In this paper, a formalization of similarity and dissimilarity is presented. The purpose of this paper is to contribute to the design and understanding of similarity and dissimilarity in AI, increasing their general utility. A formal definition and some basic properties are introduced. Also, some transformation functions and similarity and dissimilarity operators are presented.Postprint (published version
Various concepts of similarity relation have been already proposed dealing with number of coin-cided...
We study the problem of classification when only a dissimilarity function between objects is accessi...
Understanding how objects are partitioned into useful groups to form concepts is important to most d...
Similarity and dissimilarity are rarely formalized concepts in Artificial Intelligence (AI). Similar...
Intuitively, the concept of similarity is the notion to measure an inexact matching between two enti...
This work explores statistical properties of machine learning algorithms from different perspectives...
Abstract. In this work we propose a novel framework for learning a (dis)similarity function. We cast...
This paper defines the notion of analogical dissimilarity between four objects, with a special focus...
I Proliferation of machine learning algorithms in diverse domains. necessitates working with non-exp...
According to the transformational approach to similarity, two objects are judged to be more similar ...
Clustering is the process of grouping a set ofphysical or abstract objects into classes of similarob...
A pre-printMeasures of similarity (or dissimilarity) are a key ingredient to many machine learning a...
In this paper, a review about the quality of the sim-ilarity measure and its applications in machine...
We discuss definitions and properties of similarity and dissimilarity coefficients, including their ...
Similarity is a fundamental concept within Cognitive Science. It is routinely invoked in the explana...
Various concepts of similarity relation have been already proposed dealing with number of coin-cided...
We study the problem of classification when only a dissimilarity function between objects is accessi...
Understanding how objects are partitioned into useful groups to form concepts is important to most d...
Similarity and dissimilarity are rarely formalized concepts in Artificial Intelligence (AI). Similar...
Intuitively, the concept of similarity is the notion to measure an inexact matching between two enti...
This work explores statistical properties of machine learning algorithms from different perspectives...
Abstract. In this work we propose a novel framework for learning a (dis)similarity function. We cast...
This paper defines the notion of analogical dissimilarity between four objects, with a special focus...
I Proliferation of machine learning algorithms in diverse domains. necessitates working with non-exp...
According to the transformational approach to similarity, two objects are judged to be more similar ...
Clustering is the process of grouping a set ofphysical or abstract objects into classes of similarob...
A pre-printMeasures of similarity (or dissimilarity) are a key ingredient to many machine learning a...
In this paper, a review about the quality of the sim-ilarity measure and its applications in machine...
We discuss definitions and properties of similarity and dissimilarity coefficients, including their ...
Similarity is a fundamental concept within Cognitive Science. It is routinely invoked in the explana...
Various concepts of similarity relation have been already proposed dealing with number of coin-cided...
We study the problem of classification when only a dissimilarity function between objects is accessi...
Understanding how objects are partitioned into useful groups to form concepts is important to most d...