Of words in their context and ultimately generating

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Several methodologies are taken into account the analysis of the frequency of terms, the comparison of the occurrences of a keyword in proportion in several texts of the same corpus, the study of the context, etc., as well as multiple levels of language processing: lexical analysis, syntactic analysis, semantic analysis, pragmatic analysis. This is exactly how we find it in Google's applications of NLP, like its BERT algorithm.

Google and NLP: natural language processing integrated into the search engine algorithm In terms of automatic natural language processing, Google is a reference, but we will primarily focus on how this technology is used to transform BTB Directory the indexing and positioning processes of web pages. To understand how the Google algorithm evolves, we must always look at the user experience. The Mountain View firm wants to guarantee the satisfaction of Internet users who use its search engine by offering them results that are as relevant as possible, which requires continuously improving the quality of the pages highlighted in its SERP.

In this context, understanding the requests made by users is a major issue. It is no longer just a matter of grasping the overall meaning of the words, but of identifying the intention behind the search in order to better respond to it. To do this, you must understand the nuances of a query, but also detect the terms that express a “feeling”. This work by Google on NLP led to the launch, in , of the BERT algorithm – the most significant update in five years for the firm in its own words and a real leap forward in operation search engines.