Learning sentence embeddings with auxiliary tasks for cross-domain sentiment classification

• Main Authors: YU, Jianfei, JIANG, Jing
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2016
• Subjects: Benchmark datasets; Cross-domain; Joint modeling; Sentiment classification; State-of-the-art methods; Databases and Information Systems; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/3437; https://ink.library.smu.edu.sg/context/sis_research/article/4438/viewcontent/emnlp2016__2_.pdf
• Institution: Singapore Management University

In this paper, we study cross-domain sentiment classification with neural network architectures. We borrow the idea from Structural Correspondence Learning and use two auxiliary tasks to help induce a sentence embedding that supposedly works well across domains for sentiment classification. We also...