Abstract
Aspect-based sentiment analysis is currently a main focus within the domain of sentiment analysis, whose target is to identify the sentiment polarities of specific aspect terms. The ongoing research is absent of exploiting the inter-aspect relationship while mainly focus on modeling the aspect terms and its context independently. To address this problem, we propose a model integrating the conjunction information and the sentiment of the preceding aspect term. As such, the inter-aspect relation between adjacent aspect terms can be precisely modeled and applied to sentiment classification. Experimental results on SemEval 2014 and MAMS show that our model outperform the baseline methods, especially dealing with the multi-aspect terms, which establishes a strong evidence of the effectiveness of the proposed method.
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Zhao, H., Xue, Y., Gu, D., Chen, J., Xiao, L. (2021). Modeling Inter-aspect Relationship with Conjunction for Aspect-Based Sentiment Analysis. In: Karlapalem, K., et al. Advances in Knowledge Discovery and Data Mining. PAKDD 2021. Lecture Notes in Computer Science(), vol 12713. Springer, Cham. https://doi.org/10.1007/978-3-030-75765-6_60
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DOI: https://doi.org/10.1007/978-3-030-75765-6_60
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