Using autoencoders for training natural language text classifiers

A system, comprising:

• a memory;
• a processor, coupled to the memory, the processor configured to:
• produce a plurality of feature vectors, wherein each feature vector represents a natural language text of a text corpus, wherein the text corpus comprises a first plurality of annotated natural language texts and a second plurality of un-annotated natural language texts;
• train, using the plurality of feature vectors, an autoencoder represented by an artificial neural network, wherein the autoencoder comprises an input layer, a hidden layer, and an output layer;
• produce, by the autoencoder, an output of the hidden layer, by processing a training data set comprising the first plurality of annotated natural language texts;
• and
• train, using the training data set, a text classifier that accepts an input vector comprising the output of the hidden layer and yields a degree of association, with a certain text category, of a natural language text utilized to produce the output of the hidden layer.

A non-transitory computer-readable storage medium comprising executable instructions that, when executed by a computer system, cause the computer system to:

• produce a plurality of feature vectors, wherein each feature vector represents a natural language text of a text corpus, wherein the text corpus comprises a first plurality of annotated natural language texts and a second plurality of un-annotated natural language texts;
• train, using the plurality of feature vectors, an autoencoder represented by an artificial neural network, wherein the autoencoder comprises an input layer, a hidden layer, and an output layer;
• produce, by the autoencoder, an output of the hidden layer, by processing a training data set comprising the first plurality of annotated natural language texts;
• and
• train, using the training data set, a text classifier that accepts an input vector comprising the output of the hidden layer and yields a degree of association, with a certain text category, of a natural language text utilized to produce the output of the hidden layer.