计算机科学 ›› 2021, Vol. 48 ›› Issue (11): 307-311.doi: 10.11896/jsjkx.201000075
杨青, 张亚文, 朱丽, 吴涛
YANG Qing, ZHANG Ya-wen, ZHU Li, WU Tao
摘要: 针对简单的神经网络缺乏捕获文本上下文语义和提取文本内重要信息的能力,设计了一种注意力机制和门控单元(GRU)融合的情感分析模型FFA-BiAGRU。首先,对文本进行预处理,通过GloVe进行词向量化,降低向量空间维度;然后,将注意力机制与门控单元的更新门融合以形成混合模型,使其能提取文本特征中的重要信息;最后,通过强制向前注意力机制进一步提取文本特征,再由softmax分类器进行分类。在公开数据集上进行实验,结果证明该算法能有效提高情感分析的性能。
中图分类号:
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