https://wiki.apertium.org/w/index.php?action=history&feed=atom&title=Na%C3%AFve_bayes_classifier_for_lexical_selectionNaïve bayes classifier for lexical selection - Revision history2026-04-19T07:07:22ZRevision history for this page on the wikiMediaWiki 1.34.1https://wiki.apertium.org/w/index.php?title=Na%C3%AFve_bayes_classifier_for_lexical_selection&diff=32916&oldid=prevBech: Category:Documentation in English2012-03-24T11:40:39Z<p>Category:Documentation in English</p>
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</table>Bechhttps://wiki.apertium.org/w/index.php?title=Na%C3%AFve_bayes_classifier_for_lexical_selection&diff=21489&oldid=prevFrancis Tyers at 17:26, 5 October 20102010-10-05T17:26:36Z<p></p>
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<td class="diff-addedline diff-side-added"><div>==See also==</div></td>
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</table>Francis Tyershttps://wiki.apertium.org/w/index.php?title=Na%C3%AFve_bayes_classifier_for_lexical_selection&diff=21488&oldid=prevFrancis Tyers: Created page with ''''Lexical selection''' is the task of choosing the best translation of a polysemous word in a sentence. One way of doing this is to use the sentence context to determine the app…'2010-10-05T17:24:11Z<p>Created page with ''''Lexical selection''' is the task of choosing the best translation of a polysemous word in a sentence. One way of doing this is to use the sentence context to determine the app…'</p>
<p><b>New page</b></p><div>'''Lexical selection''' is the task of choosing the best translation of a polysemous word in a sentence. One way of doing this is to use the sentence context to determine the appropriate translation of a word. This context can be modelled as a '''naïve Bayes classifier'''. Lexical selection is related to [[word sense disambiguation]], and we will adopt the terminology of that field when talking about it. <br />
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[[File:Ca en paper dictionary polysemy.png|thumb|300px|right|An extract from a paper dictionary for some words in Catalan and their translations in English. Note the proper name ''Estats Units'', multiword ''L'estament mèdic'', polysemous words ''estat'', ''estar'' and ''estalviar'', and lexical-category ambiguous word ''estanc''.]]<br />
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<!--<br />
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* ''Sense'': A numerical indicator of the target language translation of a word, much like in paper dictionaries<br />
* ''<br />
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A naïve Bayes classifier is a probabilistic model of a words, senses and contexts. The contexts are represented by ''feature vectors'', which are basically other words in the sentence, and attributes of them (for example surface form, lemma, part-of-speech, etc.) In the following formula, <math>\vec{f}</math> represents a feature vector for a given sense of a word <math>s</math>.<br />
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:<math>\bar{s} = argmax ~ \frac{P(\vec{f}|s) P(s)}{P(s)}</math><br />
--></div>Francis Tyers