Journal of Shandong University(Engineering Science) ›› 2018, Vol. 48 ›› Issue (5): 47-54.doi: 10.6040/j.issn.1672-3961.0.2018.207

• Machine Learning & Data Mining • Previous Articles     Next Articles

Suggestion sentence classification model based on feature fusion and ensemble learning

Pu ZHANG1(),Chang LIU1,Yong WANG2   

  1. 1. College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
    2. Key Laboratory of Electronic Commerce and Logistics, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
  • Received:2018-05-31 Online:2018-10-01 Published:2018-05-31
  • Supported by:
    教育部人文社会科学研究青年基金资助项目(17YJCZH247);重庆市教委人文社会科学研究资助项目(17SKG055);国家自然科学基金资助项目(61472464);重庆邮电大学博士启动基金资助项目(A2016-02)

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Abstract:

As an emerging research task, suggestion mining has gradually attracted attention of researchers in recent years. Compared with English language suggestion expression forms, those of Chinese were more abundant, and many different characteristics were present. It was necessary to carry out the research on suggestion mining in the Chinese environment. As suggestion sentence detection was the core task of suggestion mining, this research proposed an ensemble learning model that integrated the Stacking and Bagging methods to classify the reviews for the detection of suggestion sentence. The model firstly used Stacking to combine classifiers and constructed probabilistic feature space. Then, the convolution neural network (CNN) and paragraph vector (PV) model were used to construct the CNN feature space and paragraph vector feature space of the reviews respectively. Finally, the above features were fused and the Bagging classifier was trained to classify suggestion sentences. Experimental results on Chinese dataset verified the effectiveness of the model.

Key words: suggestion mining, suggestion sentence classification, convolutional neural network, ensemble learning, feature fusion

CLC Number: 

  • TP391.1

Fig.1

Framework of the model"

Fig.2

Construction of probabilistic feature space"

Fig.3

Structure of Pos-TextCNN model"

Table 1

The experimental results%"

%
模型 精确率 召回率 F值 准确率
NB 83.42 81.11 82.25 82.17
FM 87.03 81.17 84.00 84.23
LR 88.58 82.05 85.19 85.20
RF 87.36 82.55 84.89 85.01
ET 86.71 83.02 84.82 84.87
TextCNN 88.14 72.10 79.32 79.70
Pos-TextCNN 84.37 79.62 81.93 81.49
Stacking+Bagging 87.48 85.20 86.32 86.25
Stacking+Bagging+CNN 87.92 84.90 86.38 86.47
Stacking+Bagging+PV 88.27 85.14 86.68 86.66
CNN+PV+Bagging 86.86 82.97 84.87 84.87
Stacking+Bagging+CNN+PV 88.63 86.06 87.33 87.28

Table 2

Classification results of confusing reviews"

序号 评论文本 NB FM LR RF ET S-B P T
1 我的9350手机升级后2天,屏幕右有条红线怎么处理,希望大神回复。 0 0 0 1 1 0 0 0
2 小小国家sx公司太欺负中国人了,我以后永远都不买他们任何一件产品,我建议全中国人都别再买,爱我中华,支持国产 0 0 1 1 1 0 0 0
3 三星c7系统更新后变成砖头了,一个月前买的三星c7当时续航能力还不错,最近系统更新后让他名不副实,原来充电一小时能充满现在充两小时都充不满而且耗电非常快,问客服说建议恢复出厂设置或者关机充电。 0 0 1 1 1 0 0 0
4 三星都有那几款,准备花4 000~5 500之间买个三星,求建议! 1 1 1 0 0 1 0 0

Table 3

Classification results of models"

序号 评论文本 NB FM LR RF ET S-B P T
1 关于指纹解锁不灵敏问题,指纹解锁实在太不灵敏了,平常都不敢开启双击启动相机。和ip6s差几个档次,和n5机皇定位严重不符。 1 1 1 0 0 1 0 0
2 三星下一代手机应该具有的特性(一个都不要少), 1.手写笔, 2.红外线遥控, 3.防水(可以游泳级别), 4.高清屏(4K,不玩VR没感受,玩了就知道了) 1 1 0 0 0 0 1 1
3 给C7更新Grace UX系统吧,很喜欢这个新的定制系统,简洁易用, C7出的时间也不长,不能不管C7。 0 0 0 0 0 0 1 1
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