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Prior knowledge solves that problem. A human encounters the same sparsity a computer does when learning from text but prior knowledge allows us to connect rare features to a larger model in which they are, in a way, less rare.

If you think about it, there is an iteration happening within machine learning that is essentially building that prior knowledge about the world by reusing previous models as inputs to knew ones. For example how Spacy uses word2vec vectors to do parsing and NER and then sense2vec uses Spacy pos tags create word vectors.

sense2vec.spacy.io