{"title":"基于贝叶斯的微博用户标签预测","authors":"Guoqiang Gao, Ruixuan Li","doi":"10.1109/WISA.2017.14","DOIUrl":null,"url":null,"abstract":"In the social network, to users, the tag is an important basis to mark and classify the resource. The tag of microblogging users can be used for advertising and network marketing. This paper presents a method based on naive Bayesian to predict the user tag. We use the user's basic attributes and some popular public tags as the features in Bayesian to predict whether a public tag belongs to a user. The experimental results show that the proposed method can achieve 87% accuracy.","PeriodicalId":204706,"journal":{"name":"2017 14th Web Information Systems and Applications Conference (WISA)","volume":"614 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Microblogging User Tag Prediction Based on Bayesian\",\"authors\":\"Guoqiang Gao, Ruixuan Li\",\"doi\":\"10.1109/WISA.2017.14\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the social network, to users, the tag is an important basis to mark and classify the resource. The tag of microblogging users can be used for advertising and network marketing. This paper presents a method based on naive Bayesian to predict the user tag. We use the user's basic attributes and some popular public tags as the features in Bayesian to predict whether a public tag belongs to a user. The experimental results show that the proposed method can achieve 87% accuracy.\",\"PeriodicalId\":204706,\"journal\":{\"name\":\"2017 14th Web Information Systems and Applications Conference (WISA)\",\"volume\":\"614 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 14th Web Information Systems and Applications Conference (WISA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WISA.2017.14\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 14th Web Information Systems and Applications Conference (WISA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WISA.2017.14","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Microblogging User Tag Prediction Based on Bayesian
In the social network, to users, the tag is an important basis to mark and classify the resource. The tag of microblogging users can be used for advertising and network marketing. This paper presents a method based on naive Bayesian to predict the user tag. We use the user's basic attributes and some popular public tags as the features in Bayesian to predict whether a public tag belongs to a user. The experimental results show that the proposed method can achieve 87% accuracy.