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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence

Knowing What, How and Why: A Near Complete Solution for Aspect-Based Sentiment Analysis

February 1, 2023

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Authors

Haiyun Peng

Alibaba Group


Lu Xu

Alibaba Group Singapore University of Technology and Design


Lidong Bing

Alibaba Group


Fei Huang

Alibaba Group


Wei Lu

Singapore University of Technology and Design


Luo Si

Alibaba Group


DOI:

10.1609/aaai.v34i05.6383


Abstract:

Target-based sentiment analysis or aspect-based sentiment analysis (ABSA) refers to addressing various sentiment analysis tasks at a fine-grained level, which includes but is not limited to aspect extraction, aspect sentiment classification, and opinion extraction. There exist many solvers of the above individual subtasks or a combination of two subtasks, and they can work together to tell a complete story, i.e. the discussed aspect, the sentiment on it, and the cause of the sentiment. However, no previous ABSA research tried to provide a complete solution in one shot. In this paper, we introduce a new subtask under ABSA, named aspect sentiment triplet extraction (ASTE). Particularly, a solver of this task needs to extract triplets (What, How, Why) from the inputs, which show WHAT the targeted aspects are, HOW their sentiment polarities are and WHY they have such polarities (i.e. opinion reasons). For instance, one triplet from “Waiters are very friendly and the pasta is simply average” could be (‘Waiters’, positive, ‘friendly’). We propose a two-stage framework to address this task. The first stage predicts what, how and why in a unified model, and then the second stage pairs up the predicted what (how) and why from the first stage to output triplets. In the experiments, our framework has set a benchmark performance in this novel triplet extraction task. Meanwhile, it outperforms a few strong baselines adapted from state-of-the-art related methods.

Topics: AAAI

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HOW TO CITE:

Haiyun Peng||Lu Xu||Lidong Bing||Fei Huang||Wei Lu||Luo Si Knowing What, How and Why: A Near Complete Solution for Aspect-Based Sentiment Analysis Proceedings of the AAAI Conference on Artificial Intelligence (2020) 8600-8607.

Haiyun Peng||Lu Xu||Lidong Bing||Fei Huang||Wei Lu||Luo Si Knowing What, How and Why: A Near Complete Solution for Aspect-Based Sentiment Analysis AAAI 2020, 8600-8607.

Haiyun Peng||Lu Xu||Lidong Bing||Fei Huang||Wei Lu||Luo Si (2020). Knowing What, How and Why: A Near Complete Solution for Aspect-Based Sentiment Analysis. Proceedings of the AAAI Conference on Artificial Intelligence, 8600-8607.

Haiyun Peng||Lu Xu||Lidong Bing||Fei Huang||Wei Lu||Luo Si. Knowing What, How and Why: A Near Complete Solution for Aspect-Based Sentiment Analysis. Proceedings of the AAAI Conference on Artificial Intelligence 2020 p.8600-8607.

Haiyun Peng||Lu Xu||Lidong Bing||Fei Huang||Wei Lu||Luo Si. 2020. Knowing What, How and Why: A Near Complete Solution for Aspect-Based Sentiment Analysis. "Proceedings of the AAAI Conference on Artificial Intelligence". 8600-8607.

Haiyun Peng||Lu Xu||Lidong Bing||Fei Huang||Wei Lu||Luo Si. (2020) "Knowing What, How and Why: A Near Complete Solution for Aspect-Based Sentiment Analysis", Proceedings of the AAAI Conference on Artificial Intelligence, p.8600-8607

Haiyun Peng||Lu Xu||Lidong Bing||Fei Huang||Wei Lu||Luo Si, "Knowing What, How and Why: A Near Complete Solution for Aspect-Based Sentiment Analysis", AAAI, p.8600-8607, 2020.

Haiyun Peng||Lu Xu||Lidong Bing||Fei Huang||Wei Lu||Luo Si. "Knowing What, How and Why: A Near Complete Solution for Aspect-Based Sentiment Analysis". Proceedings of the AAAI Conference on Artificial Intelligence, 2020, p.8600-8607.

Haiyun Peng||Lu Xu||Lidong Bing||Fei Huang||Wei Lu||Luo Si. "Knowing What, How and Why: A Near Complete Solution for Aspect-Based Sentiment Analysis". Proceedings of the AAAI Conference on Artificial Intelligence, (2020): 8600-8607.

Haiyun Peng||Lu Xu||Lidong Bing||Fei Huang||Wei Lu||Luo Si. Knowing What, How and Why: A Near Complete Solution for Aspect-Based Sentiment Analysis. AAAI[Internet]. 2020[cited 2023]; 8600-8607.


ISSN: 2374-3468


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