• Patent Title: EXPLOITING DOCUMENT KNOWLEDGE FOR ASPECT-LEVEL SENTIMENT CLASSIFICATION
  • Application No.: US16200829
    Application Date: 2018-11-27
  • Publication No.: US20200167419A1
    Publication Date: 2020-05-28
  • Inventor: Ruidan He
  • Applicant: SAP SE
  • Main IPC: G06F17/27
  • IPC: G06F17/27 G06N3/04 G06N3/08
EXPLOITING DOCUMENT KNOWLEDGE FOR ASPECT-LEVEL SENTIMENT CLASSIFICATION
Abstract:
Methods, systems, and computer-readable storage media for receiving a set of document-level training data including a plurality of documents, each document having a sentiment label associated therewith, receiving a set of aspect-level training data including a plurality of aspects, each aspect having a sentiment label associated therewith, training the aspect-level sentiment classifier including a long short-term memory (LSTM) network, and an output layer using one or more of pretraining, and multi-task learning based on the document-level training data and the aspect-level training data, pretraining including initializing parameters based on pretrained weights that are fine-tuned during training, and multi-task learning including simultaneous training of document-level classification and aspect-level classification, and providing the aspect-level sentiment classifier for classifying one or more aspects in one or more sentences of one or more input documents based on sentiment classes.
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