Document processing employing probabilistic topic modeling of documents represented as text words transformed to a continuous space

摘要: A set of word embedding transforms are applied to transform text words a documents into K-dimensional vectors in order generate sets or sequences representing the documents. probabilistic topic model is learned using The an input document sequence document. assign probabilities for topics processing operation such as annotation, classification, similar retrieval may be performed assigned probabilities.