The Classification of the Documents Based on Word Embedding and 2-layer Spherical Self Organizing Maps
The Classification of the Documents Based on Word Embedding and 2-layer Spherical Self Organizing Maps
复制标题
基于词嵌入和二层球形自组织图的文档分类
DOI：
10.1145/3318299.3318378
复制
发表时间：
2019
期刊：
影响因子：
--
通讯作者：
H. Dozono
中科院分区：
文献类型：
--
作者：
Koki Yoshioka;H. Dozono
由于社交网络的普及和网页的增加，人们可以从互联网上获取大量的文档。然而，手动处理海量的文档数据是困难的。因此，各种基于机器学习的分类方法应运而生。提出了一种基于Word2vec和球形SOM的文档关系可视化分类方法，并通过可视化实验和分类正确率的数值评估验证了该方法的性能。
Due to a popularization of SNS and increase of web pages, many documents can be obtained from the internet. However, it is difficult to process a huge set of document data manually. Therefore, various classification methods based on machine learning have been proposed. In this paper, a classification method which can visualize the relationship among the documents using Word2Vec and Spherical SOM is proposed, and the performance is examined in experiments of visualization and numerical evaluation of classification accuracy.
DOI：
10.1109/ijcnn.2010.5596524
发表时间：
2010-07
期刊：
The 2010 International Joint Conference on Neural Networks (IJCNN)
影响因子：
--
作者：
H. Matsushita;Y. Nishio
通讯作者：
H. Matsushita;Y. Nishio