DIS-C: conceptual distance in ontologies, a graph-based approach

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Abstract

© 2018, Springer-Verlag London Ltd., part of Springer Nature. This paper presents the DIS-C approach, which is a novel method to assess the conceptual distance between concepts within an ontology. DIS-C is graph based in the sense that the whole topology of the ontology is considered when computing the weight of the relationships between concepts. The methodology is composed of two main steps. First, in order to take advantage of previous knowledge, an expert of the ontology domain assigns initial weight values to each of the relations in the ontology. Then, an automatic method for computing the conceptual relations refines the weights assigned to each relation until reaching a stable state. We introduce a metric called generality that is defined in order to evaluate the accessibility of each concept, considering the ontology like a strongly connected graph. Unlike most previous approaches, the DIS-C algorithm computes similarity between concepts in ontologies that are not necessarily represented in a hierarchical or taxonomic structure. So, DIS-C is capable of incorporating a wide variety of relationships between concepts such as meronymy, antonymy, functionality and causality.
Original languageAmerican English
Pages (from-to)33-65
Number of pages26
JournalKnowledge and Information Systems
DOIs
StatePublished - 4 Apr 2019

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title = "DIS-C: conceptual distance in ontologies, a graph-based approach",
abstract = "{\circledC} 2018, Springer-Verlag London Ltd., part of Springer Nature. This paper presents the DIS-C approach, which is a novel method to assess the conceptual distance between concepts within an ontology. DIS-C is graph based in the sense that the whole topology of the ontology is considered when computing the weight of the relationships between concepts. The methodology is composed of two main steps. First, in order to take advantage of previous knowledge, an expert of the ontology domain assigns initial weight values to each of the relations in the ontology. Then, an automatic method for computing the conceptual relations refines the weights assigned to each relation until reaching a stable state. We introduce a metric called generality that is defined in order to evaluate the accessibility of each concept, considering the ontology like a strongly connected graph. Unlike most previous approaches, the DIS-C algorithm computes similarity between concepts in ontologies that are not necessarily represented in a hierarchical or taxonomic structure. So, DIS-C is capable of incorporating a wide variety of relationships between concepts such as meronymy, antonymy, functionality and causality.",
author = "Rolando Quintero and Miguel Torres-Ruiz and Rolando Menchaca-Mendez and Moreno-Armendariz, {Marco A.} and Giovanni Guzman and Marco Moreno-Ibarra",
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AU - Quintero, Rolando

AU - Torres-Ruiz, Miguel

AU - Menchaca-Mendez, Rolando

AU - Moreno-Armendariz, Marco A.

AU - Guzman, Giovanni

AU - Moreno-Ibarra, Marco

PY - 2019/4/4

Y1 - 2019/4/4

N2 - © 2018, Springer-Verlag London Ltd., part of Springer Nature. This paper presents the DIS-C approach, which is a novel method to assess the conceptual distance between concepts within an ontology. DIS-C is graph based in the sense that the whole topology of the ontology is considered when computing the weight of the relationships between concepts. The methodology is composed of two main steps. First, in order to take advantage of previous knowledge, an expert of the ontology domain assigns initial weight values to each of the relations in the ontology. Then, an automatic method for computing the conceptual relations refines the weights assigned to each relation until reaching a stable state. We introduce a metric called generality that is defined in order to evaluate the accessibility of each concept, considering the ontology like a strongly connected graph. Unlike most previous approaches, the DIS-C algorithm computes similarity between concepts in ontologies that are not necessarily represented in a hierarchical or taxonomic structure. So, DIS-C is capable of incorporating a wide variety of relationships between concepts such as meronymy, antonymy, functionality and causality.

AB - © 2018, Springer-Verlag London Ltd., part of Springer Nature. This paper presents the DIS-C approach, which is a novel method to assess the conceptual distance between concepts within an ontology. DIS-C is graph based in the sense that the whole topology of the ontology is considered when computing the weight of the relationships between concepts. The methodology is composed of two main steps. First, in order to take advantage of previous knowledge, an expert of the ontology domain assigns initial weight values to each of the relations in the ontology. Then, an automatic method for computing the conceptual relations refines the weights assigned to each relation until reaching a stable state. We introduce a metric called generality that is defined in order to evaluate the accessibility of each concept, considering the ontology like a strongly connected graph. Unlike most previous approaches, the DIS-C algorithm computes similarity between concepts in ontologies that are not necessarily represented in a hierarchical or taxonomic structure. So, DIS-C is capable of incorporating a wide variety of relationships between concepts such as meronymy, antonymy, functionality and causality.

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