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Deep learning just solves this problem. In the field of natural language processing, deep learning mechanisms allow artificial intelligence to understand the meaning of words or phrases by observing the way they are used in paragraphs. That is to say, the meaning of a word or phrase and the relationship between words are learned directly from the original paragraph, rather than through pre-defined article content or relying on human power to interpret or define the relationship. This means that when list of bahrain whatsapp phone numbers consumers search for " clear plaster " (transparent OK plaster), artificial intelligence can understand that they are looking for first-aid items, not decorative materials; this operating mechanism makes natural language processing more relevant Human learning patterns.

Sun Min pointed out that before the computer "learns the word vector represented by each independent word", the deep learning mechanism still needs to perform language learning through the analysis of a large amount of text (corpus), and these texts usually come from news websites, Wikipedia and Comments on Reddit . The concept of word vector refers to mapping similar words into vector space to observe how close they are to each other, and to determine whether different words in the same context are semantically similar.



The application of deep learning and word vectors not only enables artificial intelligence to improve the accuracy of language processing without human intervention, but also opens up a new development direction for keyword marketing and more accurate sentiment analysis.