An Ontology-Based Approach to Metaphor Cognitive Computation

Huang, Xiucheng; Huang, Huaqiong; Liao, Beishui; Xu, Chuanliang

doi:10.1007/s11023-012-9269-z

Cited by 11 publications

(4 citation statements)

References 16 publications

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“…Within this approach to the interpretation of metaphor, it has been argued that it necessarily involves comparison (Huang et al, 2013). The term "metaphor" refers to a unit consisting of two interrelated parts: "content" and "shell".…”

Section: Literature Reviewmentioning

confidence: 99%

The cognitive function of a conceptual metaphor and its methodological foundations

Beknazarova

Almautova

Yelemessova

et al. 2021

JLLS

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The theory of metaphor has gone through its development, starting with the works of Aristotle, in which it was begun, to the present state, when the linguistic paradigm became anthropocentric, and all linguistic phenomena are considered in direct connection with a person, his thinking, with society. The metaphor, which manifests the principle of human analogue thinking, occupies one of the central places in the cognitive direction of linguistic research. The cognitive theory explores metaphor as a means of conceptualising reality, as a basic mental operation that combines various conceptual spheres to explain, characterise, and cognise one with the help of the other. The novelty of the research is determined by the fact that in traditional theories (comparison theory, semantic approach) metaphor was perceived only as an unusual use of the word, as an abbreviated comparison, or investigated its semantic side, but did not pay attention to the reasons for the emergence of the metaphor, its essence, nature, its mechanisms generation, its role in the process of thinking and cognition. The authors show that the further development of the theory of metaphor is observed in close connection with the development of cognitive linguistics. The practical significance of the research is determined by the fact that the metaphor is shown not only as a phenomenon of language, but also one of the main means of thinking.

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Section: Literature Reviewmentioning

confidence: 99%

The cognitive function of a conceptual metaphor and its methodological foundations

Beknazarova

Almautova

Yelemessova

et al. 2021

JLLS

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show abstract

“…When the oscillation occurs, the damping factor can be adjusted automatically to help the algorithm get rid of the oscillation. Oscillation detection is critical to the adaptive (1).…”

Section: Convergence and Computational Complexity Analysis Of Adstreamentioning

confidence: 99%

“…The traditional computing technology is focusing on quantitative and deterministic problems, but it is not good at solving the imprecise and uncertain problems in biological systems [1]. Different from the traditional computing, cognitive computing is a new data-centric computing model.…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Density Data Stream Clustering Algorithm

et al. 2015

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Now we are in the age of big data. Huge amount of data and information are generated every time. Traditional data stream algorithms are suit for the data streams with low dimension and simple structure. However, with the development of information technology, the produced data streams are becoming more and more complicated. It is particularly important to study how to find new associations and patterns from complex data to achieve the cognition ability and judgment ability like human brain. Clustering data streams with mixed attributes of irregular distribution is a big challenge in data mining. To solve this problem, we present an adaptive density data stream clustering algorithm-ADStream. ADStream is based on the online-off-line clustering framework. It can automatically recognize the initial clusters by passing messages between data points. Then a novel time-decay density clustering strategy is designed to group and update the continuously arriving data streams. Comprehensive experimental results demonstrate that ADStream is adaptive to the evolving data streams and may generate highquality clusters with fast processing rate.

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“…There is a growing body of literature on cognitive mechanisms underlying metaphor. The paper An Ontology-Based Approach to Metaphor Cognitive Computation (Huang et al 2013) by Xiaoxi Huang, Huaxin Huang, Beishui Liao, and Cihua Xu proposes a theoretical framework for metaphor understanding based on recent results from cognitive science (Shutova 2010). They then introduce ontology as a knowledge representation method, and present a new ontological model to formalize metaphor-based knowledge.…”

mentioning

confidence: 99%

Logic and AI in China: An Introduction

Liu

2013

Minds & Machines

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An Ontology-Based Approach to Metaphor Cognitive Computation

Cited by 11 publications

References 16 publications

The cognitive function of a conceptual metaphor and its methodological foundations

The cognitive function of a conceptual metaphor and its methodological foundations

An Adaptive Density Data Stream Clustering Algorithm

Logic and AI in China: An Introduction

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