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The term semantic feature is usually used interchangeably with the term semantic component. [9] Additionally, semantic features/semantic components are also often referred to as semantic properties. [10] The theory of componential analysis and semantic features is not the only approach to analyzing the semantic structure of words. An ...
Componential analysis is a method typical of structural semantics which analyzes the components of a word's meaning. Thus, it reveals the culturally important features by which speakers of the language distinguish different words in a semantic field or domain (Ottenheimer, 2006, p. 20).
A verbal fluency test is a kind of psychological test in which a participant is asked to produce as many words as possible from a category in a given time (usually 60 seconds). This category can be semantic, including objects such as animals or fruits, or phonemic, including words beginning with a specified letter, such as p, for example. [1]
The semantic feature comparison model is used "to derive predictions about categorization times in a situation where a subject must rapidly decide whether a test item is a member of a particular target category". [1]
He argued that word sense disambiguation for machine translation should be based on the co-occurrence frequency of the context words near a given target word. The underlying assumption that "a word is characterized by the company it keeps" was advocated by J.R. Firth. [2] This assumption is known in linguistics as the distributional hypothesis. [3]
They found that Word2vec has a steep learning curve, outperforming another word-embedding technique, latent semantic analysis (LSA), when it is trained with medium to large corpus size (more than 10 million words). However, with a small training corpus, LSA showed better performance.
In linguistics, semantic analysis is the process of relating syntactic structures, from the levels of words, phrases, clauses, sentences and paragraphs to the level of the writing as a whole, to their language-independent meanings. It also involves removing features specific to particular linguistic and cultural contexts, to the extent that ...
The effect of priming on a semantic network linking can be seen through the speed of the reaction time to the word. Priming can help to reveal the structure of a semantic network and which words are most closely associated with the original word. Disruption of a semantic network can lead to a semantic deficit, not the same as semantic dementia.