Chinese Sentiment Classification Method with Bi-LSTM and Grammar Rules

被引：0

作者：

Lu Q. ^{[1
]}

Zhu Z. ^{[1
]}

Xu F. ^{[1
]}

Guo Q. ^{[1
]}

机构：

[1] School of Information Science and Electrical Engineering, Shandong Jiaotong University, Ji'nan

来源：

Data Analysis and Knowledge Discovery | 2019年 / 3卷 / 11期

关键词：

Bi-LSTM; Grammar Rules; Sentiment Classification;

D O I：

10.11925/infotech.2096-3467.2019.0412

中图分类号：

学科分类号：

摘要：

[Objective] This paper proposes a new classification method based on grammar rules, aiming to improve the accuracy of sentiment analysis for Chinese texts. [Methods] Firstly, we combined the Chinese grammar rules with Bi-LSTM in the form of constraints and standardized the adjacent positions of sentences from the experimental corpus. Then, we generated the linguistic functions of non-emotional, emotional, negative, and degree words at sentence level. [Results] Compared with the RNN, LSTM and Bi-LSTM models, the accuracy of our model reached upto 91.2%. [Limitations] The experimental data was only collected from the hotel reviews. More research is needed to examine the performance of this model on other data sets. [Conclusions] The proposed method improves the accuracy of sentiment classification for Chinese. © 2019 The Author(s).

引用

页码：99 / 107

页数：8

共 32 条

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