Fuzzy ontologies: The state of the art

Cross, Valerie

doi:10.1109/norbert.2014.6893867

Cited by 11 publications

(7 citation statements)

References 47 publications

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“…The specific lexical ontology that Resnik used was adapted from the WordNet database. Subsequent tests of the system showed it to perform well against human results [13].…”

Section: A Ontologies In Text Similaritymentioning

confidence: 97%

“…A fuzzy ontology is an ontology which uses elements of fuzzy set theory to naturally represent imprecise and vague knowledge [12]. Significant research has been undertaken to address how fuzzy set theory could be integrated into the representation of the ontology [13]. One approach relevant to this research, is in the creation of a fuzzy linguistic variable ontology where for each linguistic variable, its name, set of its associated linguistic values, binary relations between these values are ordered and stored [13].…”

Section: Fuzzy Ontologiesmentioning

confidence: 99%

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Fuzzy ontologies in semantic similarity measures

Chandran

Crockett

2016

2016 IEEE Congress on Evolutionary Computation (CEC)

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Ontologies are a fundamental part of the development of short text semantic similarity measures. The most known ontology used within the field was developed from the lexical database known as WordNet which is used as a semantic resource for determining word similarity using the semantic distance between words. The original WordNet does not include in its hierarchy fuzzy words-those which are subjective to humans and often context dependent. The recent development of fuzzy semantic similarity measures requires research into the development of different ontological structures which are suitable for the representation of fuzzy categories of words where quantification of words is undertaken by human participations. This paper proposes two different fuzzy ontology structures which are based on a human quantified scale for a collection of fuzzy words across six fuzzy categories. The methodology of ontology creation utilizes human participants to populate fuzzy categories and quantify fuzzy words. Each ontology is evaluated within a known fuzzy semantic similarity measure and experiments are conducted using human participants and two benchmark fuzzy word datasets. Correlations with human similarity ratings show only one ontological structure was naturally representative of human perceptions of fuzzy words.

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“…The specific lexical ontology that Resnik used was adapted from the WordNet database. Subsequent tests of the system showed it to perform well against human results [13].…”

Section: A Ontologies In Text Similaritymentioning

confidence: 97%

Section: Fuzzy Ontologiesmentioning

confidence: 99%

Fuzzy ontologies in semantic similarity measures

Chandran

Crockett

2016

2016 IEEE Congress on Evolutionary Computation (CEC)

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“…Fuzzy ontology is defined as the tuple <I, C, R ,F, A> [8]. I is the set of individuals, also called instances of the concepts.…”

Section: Fuzzy Ontologymentioning

confidence: 99%

“…The C: I → [0, 1] function seems to define the is-a between an instance and a concept C. F is the set of the fuzzy relations on the set of entities. A is the set of axioms defined using a suitable logical language [8].…”

Section: Fuzzy Ontologymentioning

confidence: 99%

Study of Diet Recommendation System based on Fuzzy Logic and Ontology

Chavan¹,

Sambare²

2015

IJCA

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People are becoming very conscious about their health. Universe is changing at every moment and results in seasonal variations. These seasonal variations affect on human body. Every individual having their own unique prakriti from their birth. Prakriti is one type of energy to maintain physical and mental state of human body. Imbalance in these energies results in illnesses and different diseases. For maintaining health and prevent diseases, diet is the best medicine in Ayurveda. People follow different diet plans recommended from different dietician. This recommendation is manual recommendation, in computer aided world this is taken as slow process. For recommending diet instead of manually, different approaches from computer science are used. In this paper different existing diet recommendation approaches studies based on fuzzy approaches and ontology and knowledge representation methods, and proposed a method to recommend diet based on prakriti of person and current season.

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“…It arises when analysing argumentation and the trustworthiness of conclusions. In semantics, fuzziness is introduced with the concept of 'fuzzy ontology' (Cross 2018;Cross, Chen 2018;Di Noia et al 2019), used in various domains, from medicine (Parry 2004) to news articles (Chang-Shing, Zhi-Wei, Lin-Kai 2005), but not yet applied to the archaeological discourse.…”

Section: Franco Niccoluccimentioning

confidence: 99%

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Fuzzy ontologies: The state of the art

Cited by 11 publications

References 47 publications

Fuzzy ontologies in semantic similarity measures

Fuzzy ontologies in semantic similarity measures

Study of Diet Recommendation System based on Fuzzy Logic and Ontology

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