Nursing-care Text Classification using Word Vector Representation and Convolutional Neural Networks

被引:0
作者
Nii, Manabu [1 ,3 ]
Tsuchida, Yuya [1 ]
Kato, Yusuke [2 ]
Uchinuno, Atsuko [3 ,4 ]
Sakashita, Reiko [3 ,4 ]
机构
[1] Univ Hyogo, Grad Sch Engn, Himeji, Hyogo, Japan
[2] Univ Hyogo, Sch Engn, Himeji, Hyogo, Japan
[3] JINQI, Akashi, Hyogo, Japan
[4] Univ Hyogo, Coll Nursing Art & Sci, Akashi, Hyogo, Japan
来源
2017 JOINT 17TH WORLD CONGRESS OF INTERNATIONAL FUZZY SYSTEMS ASSOCIATION AND 9TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS (IFSA-SCIS) | 2017年
关键词
Nursing-care text classification; word vector representation; convolutional neural networks;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we propose a convolutional neural network (CNN) based classification method for nursing-care classification. CNNs have obtained strong performance in computer vision speech recognition areas. Recently, CNNs have been also applied sentence classification. We have studied nursing-care text classification [6]-[18]. In our former works, we proposed several types of feature definitions and examined some classification models. In this paper, each text is represented as a concatenated word vector. Then, every text is classified using CNN-based classification methods. We examined some classification models at the classification layer in CNNs. From our experimental results, the proposed CNN-based method obtained better performance than our former works.
引用
收藏
页数:5
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