Accenture Global Solutions Limited

Jayati Deshmukh

Shubhashis Sengupta

Annervaz K M

Sanjay Podder

Neville Dubash

A system and method for transforming unstructured text into structured form is disclosed. The system and method include converting an input word sequence (e.g., sentence) into tagged output which can be then easily be converted into a structured format. The system may include a bidirectional recurrent neural network that can generate multiple labels of individual words or phrases. In some embodiments, a customized learning loss equation involving set similarity is used to generate the multiple labels.

System and method for transforming unstructured text into structured form

A device may receive information associated with first and second bug reports to be classified as duplicate or non-duplicate bug reports. The device may identify first and second descriptions associated with the first and second bug reports, respectively. The first and second descriptions may be different descriptions having a shared description type. The device may identify a neural network for encoding the first and second descriptions, based on the shared description type. The device may encode the first description into a first vector using the neural network, and may encode the second description into a second vector using the neural network. The device may classify the first and second bug reports as duplicate or non-duplicate bug reports based on the first vector and the second vector. The device may perform an action based on classifying the first and second bug reports as duplicate or non-duplicate bug reports.

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Bengaluru, India

Jayati Deshmukh