一种基于Tree-LSTM的句子相似度计算方法
An Approach of Sentence Similarity on Tree-LSTM

摘要 在浅层句法树和依存关系树的基础上, 提出两种结构化特征: 基于短语的浅层句法树NPST和基于短语的依存树NPDT, 并将它们与Tree-LSTM模型相结合, 进行句子相似度计算。实验表明, 使用结构化特征和Tree-LSTM会带来性能的提升。
Abstract Based on the shallow tree and dependency tree, the authors introduce the structural representations, NPST (new phrase-based shallow tree) and NPDT (new phrase-based dependency tree) to Tree-LSTM to compute sentence similarity. Experimental results manifest that the proposed approach achieves a higher performance than the baseline.