利用开源框架构建基于深度神经网络的短文本分类器

Building Short Text Classification with Open Source Libraries Based on Deep Neural Network

讨论了如何利用免费的开源代码库,快速构建基于深度神经网络的短文本分类器,可依照中文图书标题,将图书分类为文科和理工科两类。结果显示,文本分类器的准确率在测试集上的表现达91.9%。如果对开源社区的力量加以有效利用,能使图书馆行业充分受益。

Open source libraries are freely available online. Based on these libraries,we were able to quickly build a binary book classifier with deep neural network. The classifier will tell if a book is on liberal arts subjects or science/technology subjects. We finally get an accuracy of 91. 9% on our testing set with the classifier. We believe that the library industry will definitely benefit,if librarians can make good use of the power of open source communities.