When using the NLP API and in particular the documents.classifyText, it will obviously be classified under one of the categories listed here. My question is, do we know what was used to create these categories? Were they created from different datasets/corpora like Wikipedia, Gigaword, and Freebase? Does the Word2Vec term embedding relate to category embeddings at all? Any information, references or resources would be greatly appreciated.
By using NLP, text classification can automatically analyze text and then assign a set of predefined tags or categories based on its context. NLP is used for sentiment analysis, topic detection, and language detection. There are mainly three text classification approaches.
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