Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
12-2017
Abstract
In this paper, we study domain adaptationwith a state-of-the-art hierarchicalneural network for document-level sentimentclassification. We first design a newauxiliary task based on sentiment scoresof domain-independent words. We thenpropose two neural network architecturesto respectively induce document embeddingsand sentence embeddings that workwell for different domains. When thesedocument and sentence embeddings areused for sentiment classification, we findthat with both pseudo and external sentimentlexicons, our proposed methods canperform similarly to or better than severalhighly competitive domain adaptationmethods on a benchmark dataset of productreviews.
Discipline
Databases and Information Systems | Numerical Analysis and Scientific Computing
Research Areas
Data Science and Engineering
Publication
Proceedings of the 8th International Joint Conference on Natural Language Processing, Taipei, Taiwan, 2017 November 27 - December 1
First Page
654
Last Page
663
Publisher
ACL
City or Country
Stroudsburg, PA
Citation
YU, Jianfei and JIANG, Jing.
Leveraging auxiliary tasks for document-level cross-domain sentiment classification. (2017). Proceedings of the 8th International Joint Conference on Natural Language Processing, Taipei, Taiwan, 2017 November 27 - December 1. 654-663.
Available at: https://ink.library.smu.edu.sg/sis_research/3902
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://www.aclweb.org/anthology/I17-1066
Included in
Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons