dc.contributor.author | Sun, Mengtao | |
dc.contributor.author | Hameed, Ibrahim A. | |
dc.contributor.author | Wang, Hao | |
dc.date.accessioned | 2020-10-22T12:42:35Z | |
dc.date.available | 2020-10-22T12:42:35Z | |
dc.date.created | 2020-10-03T14:39:49Z | |
dc.date.issued | 2020 | |
dc.identifier.isbn | 978-1-7281-6926-2 | |
dc.identifier.uri | https://hdl.handle.net/11250/2684530 | |
dc.description.abstract | Text representation has a critical impact on the accuracy of text classifiers which is imperative to be strengthened. On the other hand, the question of how the state-of-the-art embeddings outperform previous approaches cannot be well explained. To advance text representation and better understand the internal mechanism, we propose a novel end-to-end framework named Ensemble Framework for Text Embedding (EFTE), which weightedly combines diverse embeddings and simultaneously represents sentences’ and tokens’ features in a more reasonable way. According to the experimental results in sentiment classification, our proposed embedding apparently improves the effectiveness compared to six single embeddings. Moreover, the importance of each embedding in terms of EFTE integration and how different embeddings influence the results by classification are discussed. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_US |
dc.relation.ispartof | Proceedings of 2020 International Joint Conference on Neural Networks (IJCNN 2020) | |
dc.title | A Novel Ensemble Representation Framework for Sentiment Classification | en_US |
dc.type | Chapter | en_US |
dc.description.version | acceptedVersion | en_US |
dc.identifier.doi | 10.1109/IJCNN48605.2020.9207194 | |
dc.identifier.cristin | 1836782 | |
dc.description.localcode | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | en_US |
cristin.ispublished | true | |
cristin.fulltext | postprint | |
cristin.qualitycode | 1 | |