{"title":"基于词嵌入和两层球面自组织图的文档分类","authors":"Koki Yoshioka, H. Dozono","doi":"10.1145/3318299.3318378","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":164987,"journal":{"name":"International Conference on Machine Learning and Computing","volume":"84 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"The Classification of the Documents Based on Word Embedding and 2-layer Spherical Self Organizing Maps\",\"authors\":\"Koki Yoshioka, H. Dozono\",\"doi\":\"10.1145/3318299.3318378\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":164987,\"journal\":{\"name\":\"International Conference on Machine Learning and Computing\",\"volume\":\"84 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-02-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Machine Learning and Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3318299.3318378\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Machine Learning and Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3318299.3318378","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Classification of the Documents Based on Word Embedding and 2-layer Spherical Self Organizing Maps
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.