Invention Grant
- Patent Title: Exploiting document knowledge for aspect-level sentiment classification
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Application No.: US16200829Application Date: 2018-11-27
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Publication No.: US10726207B2Publication Date: 2020-07-28
- Inventor: Ruidan He
- Applicant: SAP SE
- Applicant Address: DE Walldorf
- Assignee: SAP SE
- Current Assignee: SAP SE
- Current Assignee Address: DE Walldorf
- Agency: Fish & Richardson P.C.
- Main IPC: G06F40/30
- IPC: G06F40/30 ; G06N3/08 ; G06N3/04

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.
Public/Granted literature
- US20200167419A1 EXPLOITING DOCUMENT KNOWLEDGE FOR ASPECT-LEVEL SENTIMENT CLASSIFICATION Public/Granted day:2020-05-28
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