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Attention and Lexicon Regularized LSTM for Aspect-based Sentiment Analysis
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop
Attention based deep learning systems have been demonstrated to be the state of the art approach for aspect-level sentiment analysis, however, end-to-end deep neural networks lack flexibility as one can not easily adjust the network to fix an obvious problem, especially when more training data is not available: e.g. when it always predicts positive when seeing the word disappointed. Meanwhile, it is less stressed that attention mechanism is likely to "over-focus" on particular parts of adoi:10.18653/v1/p19-2035 dblp:conf/acl/BaoLB19 fatcat:oszdb5ch2nhpbi2zwnvvwkbvoi