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Given a presentation it is possible to add a new generator that is expressed as a word in the original generators. Starting with G = 〈 x | x 3 = 1 〉 and letting y = x 2 the new presentation G = 〈 x , y | x 3 = 1, y = x 2 〉 defines the same group.
An extension of word vectors for creating a dense vector representation of unstructured radiology reports has been proposed by Banerjee et al. [23] One of the biggest challenges with Word2vec is how to handle unknown or out-of-vocabulary (OOV) words and morphologically similar words. If the Word2vec model has not encountered a particular word ...
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Regular languages are a category of languages (sometimes termed Chomsky Type 3) which can be matched by a state machine (more specifically, by a deterministic finite automaton or a nondeterministic finite automaton) constructed from a regular expression.
In languages with V2 word order, such as most Germanic languages except for Modern English, as well as Ingush and Oʼodham, the verb is always the second element in a main clause. The subject precedes the verb by default, but if another word or phrase is put at the front of the clause, the subject is moved to the position immediately after the ...
Word frequency is known to have various effects (Brysbaert et al. 2011; Rudell 1993). Memorization is positively affected by higher word frequency, likely because the learner is subject to more exposures (Laufer 1997). Lexical access is positively influenced by high word frequency, a phenomenon called word frequency effect (Segui et al.).
The bag-of-words model (BoW) is a model of text which uses an unordered collection (a "bag") of words. It is used in natural language processing and information retrieval (IR). It disregards word order (and thus most of syntax or grammar) but captures multiplicity .
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