iOS gives us the ability to search for similar words for a term by using word embeddings, which are maps of strings created using machine learning that describe how similar various words are in terms of their meaning. This kind of thing is useful when handling user searches: you might have tagged a photo with “hat”, but your user searched for “sombrero” – word embeddings let us find similar words, and we can then use those variations for data searches.... Continue Reading >>
Apple’s NaturalLanguage framework is able to lemmatize text for us, which is the process of converting words to the forms you would find in a dictionary – making plural nouns singular, finding the root forms of conjugated verbs, and so on, while also taking into account the context in which they are used.... Continue Reading >>
Sentiment analysis uses machine learning to tell us whether a piece of text is considered positive or negative, and it’s baked right in to iOS with the NaturalLanguage framework.... Continue Reading >>
This is part of the Swift Knowledge Base, a free, searchable collection of solutions for common iOS questions, all written for Swift 5.4.
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