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Proceedings of the 33rd International Conference on Software Engineering and Knowledge Engineering
Recently, most relational extraction models usually mitigate the adverse effects of noise in sentences for the prediction results, utilizing different tools of natural language processing that to capture high-level features in sentences combined. However, these attention mechanisms do not manage to exploit as much as possible the semantic information of certain keywords that have relational expressive information in the sentence. Therefore, this paper proposes a model based on the keyword'sdoi:10.18293/seke2021-073 fatcat:khchu7hm75gmjii5dsgmzf66p4