Dependency tree and attention mechanism-based attribute sentiment classification method

The invention discloses a dependency tree and attention mechanism-based attribute sentiment classification method. The method comprises the steps of selecting a smallest sub-tree part comprising givenattributes based on a dependency tree analysis result of a whole text, and taking clauses of the part as representations of context information of the attributes; then performing modeling on contextsof sentences and contexts of the attributes by utilizing two bidirectional threshold circulation units to obtain two feature representation matrixes fixed in size; obtaining feature representations of the text and specific attributes by utilizing an attention mechanism; and finally performing sentiment polarity classification of the specific attributes by utilizing a multilayer perceptron. The classification method proposed by the invention can extract different attribute feature information for different attributes in the same text, and is high in classification accuracy. 本发明公开了种基于依存树和注意力机制的属性情感分类方法，基于整个文本的依存树分析结果，选择