When analyzing queries together

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Rakhiexpatebd
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When analyzing queries together

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Or reserve Homonymy -words that have different meanings, and sometimes also represent a different part of speech and, unlike polysemic expressions, have no dependencies. This is a significant obstacle for AI, when, for example, the word "function" can mean performing some role, mathematical concept or property. Synonymy - words that mean the same as another word or are semantically similar. Text analysis is difficult because synonyms are separate words. A synonym for "small" may be "mini". What does Google display when we enter "little dog" in the search engine? Using the synonym of this expression in the form of "mini dog" we ge.

Even though BERT has been learning since , he still doesn't understand Mexico WhatsApp Number List the difference between a "mini dog" and a "mini pie". Admittedly, in similar searches, it suggests that it may be a 'mini dog'. Idiomaticity - constructions that cannot be literally analyzed or translated into another language: "it rains cats and dogs" does not mean rain of dogs and cats, but knowing the words "it," "rains," "cats," "and" , "dogs" without linguistic awareness it would not be so obvious. Context – the main role in understanding language messages is played by the context.

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The sentence "Veronika borrowed the car" could mean that Veronica lent the car to someone else or that she borrowed the car from someone. Recognition of goals, intentions or plans is a prerequisite for the correct interpretation of the query, which is why before the introduction of the BERT update, it was predicted that it would affect about % of search results. Corereference – that is, the relationship between what is said about: "He took the cheese out of the fridge and put it on the sandwich." AI loses its orientation in content with a lot of pronouns and references. The update was primarily intended to improve the quality of responses to long-tail searches, but also to keyword searches.
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