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Semantic mapping or semantic webbing, in literacy, is a method of teaching reading using graphical representations of concepts and the relationships between them. [1] [2]
A sentence diagram is a pictorial representation of the grammatical structure of a sentence. The term "sentence diagram" is used more when teaching written language, where sentences are diagrammed. The model shows the relations between words and the nature of sentence structure and can be used as a tool to help recognize which potential ...
Bitext word alignment finds out corresponding words in two texts. Bitext word alignment or simply word alignment is the natural language processing task of identifying translation relationships among the words (or more rarely multiword units) in a bitext, resulting in a bipartite graph between the two sides of the bitext, with an arc between two words if and only if they are translations of ...
A common alternative to using dictionaries is the hashing trick, where words are mapped directly to indices with a hashing function. [5] Thus, no memory is required to store a dictionary. Hash collisions are typically dealt via freed-up memory to increase the number of hash buckets [clarification needed]. In practice, hashing simplifies the ...
Once trained, such a model can detect synonymous words or suggest additional words for a partial sentence. Word2vec was developed by Tomáš Mikolov and colleagues at Google and published in 2013. Word2vec represents a word as a high-dimension vector of numbers which capture relationships between words.
Diesendruck (2007) characterized these different mapping proposals as being on two dimensions: specificity to word learning and the source of support for word learning. For specificity to word learning, knowledge of lexical constraints is only useful for learning new words whereas attention to novelty is a characteristic of attention that ...
A concept map or conceptual diagram is a diagram that depicts suggested relationships between concepts. [1] Concept maps may be used by instructional designers, engineers, technical writers, and others to organize and structure knowledge.
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]