Graph Convolutional Neural Networks For Sentiment Analysis
| but.event.date | 23.04.2020 | cs |
| but.event.title | Student EEICT 2020 | cs |
| dc.contributor.author | Myska, Vojtech | |
| dc.date.accessioned | 2021-07-15T11:17:22Z | |
| dc.date.available | 2021-07-15T11:17:22Z | |
| dc.date.issued | 2020 | cs |
| dc.description.abstract | Commonly used approaches based on deep learning for sentiment analysis task operating over data in Euclidean space. In contrast with them, this paper presents, a novel approach for sentiment analysis task based on a graph convolutional neural networks (GCNs) operating with data in Non-Euclidean space. Text data processed by the approach have to be converted to a graph structure. Our GCNs models have been trained on 25 000 data samples and evaluated 5 000 samples. The Yelp data set has been used. The experiment is focused on polarity sentiment analysis task. Nevertheless, a relatively small training data set has been used, our best model achieved 86.12% accuracy. | en |
| dc.format | text | cs |
| dc.format.extent | 340-344 | cs |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | Proceedings I of the 26st Conference STUDENT EEICT 2020: General papers. s. 340-344. ISBN 978-80-214-5867-3 | cs |
| dc.identifier.isbn | 978-80-214-5867-3 | |
| dc.identifier.uri | http://hdl.handle.net/11012/200592 | |
| dc.language.iso | en | cs |
| dc.publisher | Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií | cs |
| dc.relation.ispartof | Proceedings I of the 26st Conference STUDENT EEICT 2020: General papers | en |
| dc.relation.uri | https://conf.feec.vutbr.cz/eeict/EEICT2020 | cs |
| dc.rights | © Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií | cs |
| dc.rights.access | openAccess | en |
| dc.subject | sentiment analysis | en |
| dc.subject | graph neural networks | en |
| dc.subject | deep learning | en |
| dc.title | Graph Convolutional Neural Networks For Sentiment Analysis | en |
| dc.type.driver | conferenceObject | en |
| dc.type.status | Peer-reviewed | en |
| dc.type.version | publishedVersion | en |
| eprints.affiliatedInstitution.department | Fakulta elektrotechniky a komunikačních technologií | cs |
Files
Original bundle
1 - 1 of 1
Loading...
- Name:
- 340-eeict_1.pdf
- Size:
- 751.19 KB
- Format:
- Adobe Portable Document Format
- Description: