Hierarchical classification using neural networks

A system comprising one or more computers and one or more storage devices storing instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising:

• processing a source sequence of inputs corresponding to an input text block with an encoder recurrent neural network (RNN) to generate a respective encoder hidden state for each input;
• processing the respective encoder hidden states with a decoder RNN to produce a sequence of outputs representing a classification path in a multi-level hierarchical classification taxonomy for the input text block;
• wherein the sequence of outputs is produced, in an output order, from a predetermined vocabulary of outputs representing respective class nodes in a directed acyclic graph representation of the multi-level hierarchical classification taxonomy.

One or more non-transitory computer storage media encoded with a computer program product comprising instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising:

• processing a source sequence of inputs corresponding to an input text block with an encoder recurrent neural network (RNN) to generate a respective encoder hidden state for each input;
• processing the respective encoder hidden states with a decoder RNN to produce a sequence of outputs representing a classification path in a multi-level hierarchical classification taxonomy for the input text block;
• wherein the sequence of outputs is produced, in an output order, from a predetermined vocabulary of outputs representing respective class nodes in a directed acyclic graph representation of the multi-level hierarchical classification taxonomy.