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The output of a word-sense induction algorithm is a clustering of contexts in which the target word occurs or a clustering of words related to the target word. Three main methods have been proposed in the literature: [1] [2] Context clustering; Word clustering; Co-occurrence graphs
word-sense induction – the task of automatically acquiring the senses of a target word; word-sense disambiguation – the task of automatically associating a sense with a word in context; lexical substitution – the task of replacing a word in context with a lexical substitute; sememe – unit of meaning
Versions have been adapted to use WordNet. [2] An implementation might look like this: for every sense of the word being disambiguated one should count the number of words that are in both the neighborhood of that word and in the dictionary definition of that sense; the sense that is to be chosen is the sense that has the largest number of this ...
On finer-grained sense distinctions, top accuracies from 59.1% to 69.0% have been reported in evaluation exercises (SemEval-2007, Senseval-2), where the baseline accuracy of the simplest possible algorithm of always choosing the most frequent sense was 51.4% and 57%, respectively.
WordNet aims to cover most everyday words and does not include much domain-specific terminology. WordNet is the most commonly used computational lexicon of English for word-sense disambiguation (WSD), a task aimed at assigning the context-appropriate meanings (i.e. synset members) to words in a text. [14]
[2] The article "The Science of Word Recognition" says that "evidence from the last 20 years of work in cognitive psychology indicates that we use the letters within a word to recognize a word". Over time, other theories have been put forth proposing the mechanisms by which words are recognized in isolation, yet with both speed and accuracy. [ 3 ]
Word2vec is a group of related models that are used to produce word embeddings.These models are shallow, two-layer neural networks that are trained to reconstruct linguistic contexts of words.
Lexical semantics (also known as lexicosemantics), as a subfield of linguistic semantics, is the study of word meanings. [1] [2] It includes the study of how words structure their meaning, how they act in grammar and compositionality, [1] and the relationships between the distinct senses and uses of a word.
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