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  2. Semantic feature - Wikipedia

    en.wikipedia.org/wiki/Semantic_feature

    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 ...

  3. Statistical semantics - Wikipedia

    en.wikipedia.org/wiki/Statistical_semantics

    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]

  4. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    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.

  5. Componential analysis - Wikipedia

    en.wikipedia.org/wiki/Componential_analysis

    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).

  6. Word embedding - Wikipedia

    en.wikipedia.org/wiki/Word_embedding

    In natural language processing, a word embedding is a representation of a word. The embedding is used in text analysis.Typically, the representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be similar in meaning. [1]

  7. Semantic network - Wikipedia

    en.wikipedia.org/wiki/Semantic_network

    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 to be confused with as ...

  8. Explicit semantic analysis - Wikipedia

    en.wikipedia.org/wiki/Explicit_semantic_analysis

    The name "explicit semantic analysis" contrasts with latent semantic analysis (LSA), because the use of a knowledge base makes it possible to assign human-readable labels to the concepts that make up the vector space. [1] [3]

  9. SemEval - Wikipedia

    en.wikipedia.org/wiki/SemEval

    The first major area in semantic analysis is the identification of the intended meaning at the word level (taken to include idiomatic expressions). This is word-sense disambiguation (a concept that is evolving away from the notion that words have discrete senses, but rather are characterized by the ways in which they are used, i.e., their ...