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  2. Word-sense induction - Wikipedia

    en.wikipedia.org/wiki/Word-sense_induction

    Word clustering is a different approach to the induction of word senses. It consists of clustering words, which are semantically similar and can thus bear a specific meaning. Lin’s algorithm [5] is a prototypical example of word clustering, which is based on syntactic dependency statistics, which occur in a corpus to produce sets of words for ...

  3. Word sense - Wikipedia

    en.wikipedia.org/wiki/Word_sense

    In linguistics, a word sense is one of the meanings of a word. For example, a dictionary may have over 50 different senses of the word "play", each of these having a different meaning based on the context of the word's usage in a sentence, as follows: We went to see the play Romeo and Juliet at the theater.

  4. Word-sense disambiguation - Wikipedia

    en.wikipedia.org/wiki/Word-sense_disambiguation

    Word-sense disambiguation is the process of identifying which sense of a word is meant in a sentence or other segment ... Identification of dominant word senses; [41 ...

  5. Classic monolingual word-sense disambiguation - Wikipedia

    en.wikipedia.org/wiki/Classic_monolingual_word...

    The reason for adopting a previously unknown sense inventory was mainly to avoid the use of popular fine-grained word senses (such as WordNet), which could make the experiments unfair or biased. However, given the lack of coverage of such inventories, since the second Senseval workshop the WordNet sense inventory has been adopted.

  6. Yarowsky algorithm - Wikipedia

    en.wikipedia.org/wiki/Yarowsky_algorithm

    In computational linguistics the Yarowsky algorithm is an unsupervised learning algorithm for word sense disambiguation that uses the "one sense per collocation" and the "one sense per discourse" properties of human languages for word sense disambiguation. From observation, words tend to exhibit only one sense in most given discourse and in a ...

  7. Lesk algorithm - Wikipedia

    en.wikipedia.org/wiki/Lesk_algorithm

    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 count. A frequently used example illustrating this algorithm is for the context "pine ...

  8. Lexical substitution - Wikipedia

    en.wikipedia.org/wiki/Lexical_substitution

    Lexical substitution is strictly related to word sense disambiguation (WSD), in that both aim to determine the meaning of a word. However, while WSD consists of automatically assigning the appropriate sense from a fixed sense inventory, lexical substitution does not impose any constraint on which substitute to choose as the best representative ...

  9. Reading - Wikipedia

    en.wikipedia.org/wiki/Reading

    Reading is the process of taking in the sense or meaning of symbols, often specifically those of a written language, by means of sight or touch. [1] [2] [3] [4]For educators and researchers, reading is a multifaceted process involving such areas as word recognition, orthography (spelling), alphabetics, phonics, phonemic awareness, vocabulary, comprehension, fluency, and motivation.

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