Cross-domain emotion classification system and method based on hierarchical attention mechanism

The invention relates to a cross-domain emotion classification system based on a hierarchical attention mechanism, and the system comprises a text preprocessing module which is used for the characterization of a cross-domain text; a pivot feature extraction module, used for learning a feature representation space adapted to the field to obtain pivot feature document representation of the source field and the target field; a non-pivot feature extraction module, used for acquiring non-pivot feature representation; and an emotion category output module, used for obtaining a final emotion classification result. According to the method, efficient cross-domain emotion classification is realized, the cross-domain emotion classification precision is improved, and the consumption of manual time andenergy is reduced. 本发明涉及一种基于分层注意力机制的跨领域情感分类系统，包括：文本预处理模块，用于对跨领域文本进行特征化处理；枢轴特征提取模块，用于学习领域适应的特征表示空间，得到源领域与目标领域的枢轴特征文档表示；非枢轴特征提取模块，用于获取非枢轴特征表示；情感类别输出模块，用于获取最终的情感分类结果。本发明实现了高效的跨领域情感分类，提高了跨领域情感分类精度并减少人工时间精力的消耗。