Abstract
We propose a phrase-based approach for generating product review summaries. The main idea of our method is to leverage phrase properties to choose a subset of optimal phrases for generating the final summary. Specifically, we exploit two phrase properties, popularity and specificity. Popularity describes how popular the phrase is in the original reviews. Specificity describes how descriptive a phrase is in comparison to generic comments. We formalize the phrase selection procedure as an optimization problem and solve it using integer linear programming (ILP). An aspect-based bigram language model is used for generating the final summary with the selected phrases. Experiments show that our summarizer outperforms the other baselines.- Anthology ID:
- C16-1106
- Volume:
- Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
- Month:
- December
- Year:
- 2016
- Address:
- Osaka, Japan
- Editors:
- Yuji Matsumoto, Rashmi Prasad
- Venue:
- COLING
- SIG:
- Publisher:
- The COLING 2016 Organizing Committee
- Note:
- Pages:
- 1113–1124
- Language:
- URL:
- https://aclanthology.org/C16-1106
- DOI:
- Cite (ACL):
- Naitong Yu, Minlie Huang, Yuanyuan Shi, and Xiaoyan Zhu. 2016. Product Review Summarization by Exploiting Phrase Properties. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 1113–1124, Osaka, Japan. The COLING 2016 Organizing Committee.
- Cite (Informal):
- Product Review Summarization by Exploiting Phrase Properties (Yu et al., COLING 2016)
- PDF:
- https://preview.aclanthology.org/bionlp-24-ingestion/C16-1106.pdf