Results 271 to 280 of about 7,273,685 (301)
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Semantic hidden Markov networks
2nd International Conference on Spoken Language Processing (ICSLP 1992), 1992Although much effort has been put into speech understanding systems there still exists a rather wide gap between acoustic recognition and linguistic interpretation. We propose a formalism for an extremely close interaction of acoustic recognition and higher level analysis.
Fink, Gernot A. +4 more
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Distant connectivity and multiple-step priming in large-scale semantic networks.
Journal of Experimental Psychology. Learning, Memory and Cognition, 2019We examined 3 different network models of representing semantic knowledge (5,018-word directed and undirected step distance networks, and an association-correlation network) to predict lexical priming effects.
Abhilasha Ashok Kumar +2 more
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Cognition, 1991
Principles of lexical semantics developed in the course of building an on-line lexical database are discussed. The approach is relational rather than componential. The fundamental semantic relation is synonymy, which is required in order to define the lexicalized concepts that words can be used to express.
G A, Miller, C, Fellbaum
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Principles of lexical semantics developed in the course of building an on-line lexical database are discussed. The approach is relational rather than componential. The fundamental semantic relation is synonymy, which is required in order to define the lexicalized concepts that words can be used to express.
G A, Miller, C, Fellbaum
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International Journal of Science Education, 2018
Just as language reflects one’s thoughts, the text of science textbooks reflects the structure of scientific knowledge and thought. Therefore, students’ learning of scientific language leads to their acquisition of the structure of scientific knowledge ...
E. Yun, Y. Park
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Just as language reflects one’s thoughts, the text of science textbooks reflects the structure of scientific knowledge and thought. Therefore, students’ learning of scientific language leads to their acquisition of the structure of scientific knowledge ...
E. Yun, Y. Park
semanticscholar +1 more source
Structures of Semantic Networks: Similarities between Semantic Networks and Brain Networks
2006 5th IEEE International Conference on Cognitive Informatics, 2006Two networks were extracted from two large semantic networks, HowNet and synsets of WordNet, based on conceptual relations. Analysis of these networks shows that they are complex networks with features of small-world and scale-free. Results also show that semantic networks are similar to brain networks: (a) exponents of power law degree distributions ...
Lu Tang, Yong Guang Zhang, Xue Fu
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Semantic relatedness in semantic networks
2008This paper presents a new semantic relatedness measure on semantic networks (SN) that uses both hierarchical and non-hierarchical relations. Our approach relies on two assumptions. Firstly, in a given SN, only a few numbers of paths can be considered as “semantically correct” and these paths obey to a given set of rules.
Mazuel, Laurent, Sabouret, Nicolas
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International Journal of Modern Physics C, 2010
Verbal language is a dynamic mental process. Ideas emerge by means of the selection of words from subjective and individual characteristics throughout the oral discourse. The goal of this work is to characterize the complex network of word associations that emerge from an oral discourse from a discourse topic.
G. M. TEIXEIRA +7 more
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Verbal language is a dynamic mental process. Ideas emerge by means of the selection of words from subjective and individual characteristics throughout the oral discourse. The goal of this work is to characterize the complex network of word associations that emerge from an oral discourse from a discourse topic.
G. M. TEIXEIRA +7 more
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2019
In spite of the fact that BN is inherently capable of representing, learning, and reasoning with uncertain knowledge , the performance of BN highly depends on the size of available training dataset. A proper learning of the network needs large amount of observed data be available during the training procedure.
Monidipa Das, Soumya K. Ghosh
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In spite of the fact that BN is inherently capable of representing, learning, and reasoning with uncertain knowledge , the performance of BN highly depends on the size of available training dataset. A proper learning of the network needs large amount of observed data be available during the training procedure.
Monidipa Das, Soumya K. Ghosh
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Semantic Flow Networks: Semantic Interoperability in Networks of Ontologies
2011Ontology ...
Fionda, Valeria, Pirrò, Giuseppe
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