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Cone : unsupervised contrastive opinion extraction
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Zhao, Runcong, Gui, Lin and He, Yulan (2023) Cone : unsupervised contrastive opinion extraction. In: SIGIR '23 : 46th International ACM SIGIR Conference on Research and Development in Information Retrieval. Published in: SIGIR '23: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval pp. 1066-1075. doi:10.1145/3539618.3591650
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Official URL: http://dx.doi.org/10.1145/3539618.3591650
Abstract
Contrastive opinion extraction aims to extract a structured summary or key points organised as positive and negative viewpoints towards a common aspect or topic. Most recent works for unsupervised key point extraction is largely built on sentence clustering or opinion summarisation based on the popularity of opinions expressed in text. However, these methods tend to generate aspect clusters with incoherent sentences, conflicting viewpoints, redundant aspects. To address these problems, we propose a novel unsupervised Contrastive OpinioN Extraction model, called Cone, which learns disentangled latent aspect and sentiment representations based on pseudo aspect and sentiment labels by combining contrastive learning with iterative aspect/sentiment clustering refinement. Apart from being able to extract contrastive opinions, it is also able to quantify the relative popularity of aspects and their associated sentiment distributions. The model has been evaluated on both a hotel review dataset and a Twitter dataset about COVID vaccines. The results show that despite using no label supervision or aspect-denoted seed words, Cone outperforms a number of competitive baselines on contrastive opinion extraction. The results of Cone can be used to offer a better recommendation of products and services online.
Item Type: | Conference Item (Paper) | ||||
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||
Journal or Publication Title: | SIGIR '23: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval | ||||
Book Title: | Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval | ||||
Official Date: | 18 July 2023 | ||||
Dates: |
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Page Range: | pp. 1066-1075 | ||||
DOI: | 10.1145/3539618.3591650 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access | ||||
Conference Paper Type: | Paper | ||||
Title of Event: | SIGIR '23 : 46th International ACM SIGIR Conference on Research and Development in Information Retrieval | ||||
Type of Event: | Conference |
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