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Runaway1956 writes:

Google is currently rolling out a change to its core search algorithm that it says could change the rankings of results for as many as one in ten queries. It's based on cutting-edge natural language processing (NLP) techniques developed by Google researchers and applied to its search product over the course of the past 10 months.

In essence, Google is claiming that it is improving results by having a better understanding of how words relate to each other in a sentence. In one example Google discussed at a briefing with journalists yesterday, its search algorithm was able to parse the meaning of the following phrase: "Can you get medicine for someone pharmacy?"

The old Google search algorithm treated that sentence as a "bag of words," according to Pandu Nayak, Google fellow and VP of search. So it looked at the important words, medicine and pharmacy, and simply returned local results. The new algorithm was able to understand the context of the words "for someone" to realize it was a question about whether you could pick up somebody else's prescription — and it returned the right results.

The tweaked algorithm is based on BERT, which stands for "Bidirectional Encoder Representations from Transformers." Every word of that acronym is a term of art in NLP, but the gist is that instead of treating a sentence like a bag of words, BERT looks at all the words in the sentence as a whole. Doing so allows it to realize that the words "for someone" shouldn't be thrown away, but rather are essential to the meaning of the sentence.

https://www.theverge.com/2019/10/25/20931657/google-bert-search-context-algorithm-change-10-percent-langauge

I can't help wondering how this is handled in other languages. Chinese, for instance, where (I've read that) a word might have several meanings, but context defines the word.

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