A Data-Driven Approach to Constructing an Ontological Concept Hierarchy Based on the Formal Concept Analysis

Hwang, Suk-Hyung; Kim, Hong-Gee; Kim, Myeng-Ki; Choi, Sung-Hee; Yang, Hae-Sool

doi:10.1007/11751632_101

Cited by 4 publications

(2 citation statements)

References 2 publications

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“…concepts and subsumption relationships between them [19]. A concept hierarchy defines a sequence of mappings from a set of lower-level concepts to their higher-level correspondences.…”

Section: Ontologies Concept Hierarchies and Semantic Relationsmentioning

confidence: 99%

An intelligent system for semi-automatic evolution of ontologies

Ramezani¹,

Witschel²

2010

2010 5th IEEE International Conference Intelligent Systems

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Ontologies are an important part of the Semantic Web as well as of many intelligent systems. However, the traditional expert-driven development of ontologies is time-consuming and often results in incomplete and inappropriate ontologies. In addition, since ontology evolution is not controlled by end users, it may take too long for a conceptual change in the domain to be reflected in the ontology. In this paper, we present a recommendation algorithm in a Web 2.0 platform that supports end users to collaboratively evolve ontologies by suggesting semantic relations between new and existing concepts. We use the Wikipedia category hierarchy to evaluate our algorithm and our experimental results show that the proposed algorithm produces high quality recommendations.

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“…concepts and subsumption relationships between them [19]. A concept hierarchy defines a sequence of mappings from a set of lower-level concepts to their higher-level correspondences.…”

Section: Ontologies Concept Hierarchies and Semantic Relationsmentioning

confidence: 99%

An intelligent system for semi-automatic evolution of ontologies

Ramezani¹,

Witschel²

2010

2010 5th IEEE International Conference Intelligent Systems

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“…Formal concept analysis (FCA) has been used to help automate the construction of ontologies [12] [13] [14]. FCA is an unsupervised learning method widely used for knowledge discovery [15] that clusters data to create concepts.…”

Section: B Creating Fuzzy Ontologiesmentioning

confidence: 99%

Fuzzy ontologies: The state of the art

Cross

2014

2014 IEEE Conference on Norbert Wiener in the 21st Century (21CW)

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Ontologies play a central role in the SemanticWeb. Much research has focused on extending ontologies and Semantic Web technologies to handle uncertain information. This paper provides a review of recent approaches for extending ontologies to fuzzy ontologies. Some approaches have been developed for application specific purposes, for example for information retrieval and search on the Semantic Web and are not formally relying on current Semantic Web technologies such as standard web ontology languages and tools such as ontology editors or reasoners. Other approaches emphasize developing methods to extend Semantic Web standard technologies with fuzzy logic and fuzzy reasoning.

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Fuzzy concept lattice construction: A basis for building fuzzy ontologies

Cross

Kandasamy

2011

2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011)

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A Data-Driven Approach to Constructing an Ontological Concept Hierarchy Based on the Formal Concept Analysis

Cited by 4 publications

References 2 publications

An intelligent system for semi-automatic evolution of ontologies

An intelligent system for semi-automatic evolution of ontologies

Fuzzy ontologies: The state of the art

Fuzzy concept lattice construction: A basis for building fuzzy ontologies

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