Attribute-aware Sequence Network for Review Summarization

Junjie Li, Xuepeng Wang, Dawei Yin, Chengqing Zong

Abstract
Review summarization aims to generate a condensed summary for a review or multiple reviews. Existing review summarization systems mainly generate summary only based on review content and neglect the authors’ attributes (e.g., gender, age, and occupation). In fact, when summarizing a review, users with different attributes usually pay attention to specific aspects and have their own word-using habits or writing styles. Therefore, we propose an Attribute-aware Sequence Network (ASN) to take the aforementioned users’ characteristics into account, which includes three modules: an attribute encoder encodes the attribute preferences over the words; an attribute-aware review encoder adopts an attribute-based selective mechanism to select the important information of a review; and an attribute-aware summary decoder incorporates attribute embedding and attribute-specific word-using habits into word prediction. To validate our model, we collect a new dataset TripAtt, comprising 495,440 attribute-review-summary triplets with three kinds of attribute information: gender, age, and travel status. Extensive experiments show that ASN achieves state-of-the-art performance on review summarization in both auto-metric ROUGE and human evaluation.
Anthology ID:
D19-1297
Volume:
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
Month:
November
Year:
2019
Address:
Hong Kong, China
Editors:
Kentaro Inui, Jing Jiang, Vincent Ng, Xiaojun Wan
Venues:
EMNLP | IJCNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
3000–3010
Language:
URL:
https://aclanthology.org/D19-1297
DOI:
10.18653/v1/D19-1297
Bibkey:
Cite (ACL):
Junjie Li, Xuepeng Wang, Dawei Yin, and Chengqing Zong. 2019. Attribute-aware Sequence Network for Review Summarization. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 3000–3010, Hong Kong, China. Association for Computational Linguistics.
Cite (Informal):
Attribute-aware Sequence Network for Review Summarization (Li et al., EMNLP-IJCNLP 2019)
Copy Citation:
PDF:
https://preview.aclanthology.org/naacl24-info/D19-1297.pdf
PDF Search