| Title | Cross-domain Aspect/Sentiment-aware Abstractive Review Summarization |
| Authors | Yang, Min Qu, Qiang Zhu, Jia Shen, Ying Zhao, Zhou |
| Affiliation | Chinese Acad Sci, SIAT, Shenzhen, Peoples R China. South China Normal Univ, Guangzhou, Guangdong, Peoples R China. Peking Univ, Shenzhen Grad Sch, Shenzhen, Peoples R China. Zhejiang Univ, Hangzhou, Zhejiang, Peoples R China. |
| Keywords | Abstractive Review Summarization Topic Modeling Domain adaptation |
| Issue Date | 2018 |
| Publisher | CIKM'18: PROCEEDINGS OF THE 27TH ACM INTERNATIONAL CONFERENCE ON INFORMATION AND KNOWLEDGE MANAGEMENT |
| Citation | CIKM'18: PROCEEDINGS OF THE 27TH ACM INTERNATIONAL CONFERENCE ON INFORMATION AND KNOWLEDGE MANAGEMENT. 2018, 1531-1534. |
| Abstract | This study takes the lead to study the aspect/sentiment-aware abstractive review summarization in domain adaptation scenario. The proposed model CASAS (neural attentive model for Cross-domain Aspect/Sentiment-aware Abstractive review Summarization) leverages domain classification task, working on datasets of both source and target domains, to recognize the domain information of texts and transfer knowledge from source domains to target domains. The extensive experiments on Amazon reviews demonstrate that CASAS outperforms the compared methods in both out-of-domain and in-domain setups. |
| URI | http://hdl.handle.net/20.500.11897/571602 |
| DOI | 10.1145/3269206.3269273 |
| Indexed | CPCI-S(ISTP) |
| Appears in Collections: | 深圳研究生院待认领 |
