首页|Research on semantic similarity calculation methods in Chinese financial intelligent customer service
Research on semantic similarity calculation methods in Chinese financial intelligent customer service
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NSTL
Semantic similarity computing is an important task in NLP, which aims to calculate the semantic similarity between texts. In order to solve the problem of low accuracy of existing calculation methods in Chinese financial intelligent customer services, we propose a text similarity calculation method combining Capsule-BiLSTM network and Chinese Part of Speech (POS) correction. In the text pre-processing stage, POS correction is performed on financial professional words and ambiguous words in the data set to reduce the influence of Chinese word segmentation errors on similarity judgments. Capsule network and BiLSTM were used to obtain local and global information, respectively, the two similarity matrices obtained are fused to determine the similarity. Experimental results show that the proposed method compared with other conventional methods has high precision and F1-value in ATEC data set.
semantic similaritycapsule networkBiLSTMpart of speech correctionSYSTEM
NSTL
