{"title":"The research on the automatic generation of micro-blog user tags based on clustering analysis","authors":"Haiyan Lv, Xiaowei Che, Ren Ying","doi":"10.1109/ICSESS.2014.6933648","DOIUrl":null,"url":null,"abstract":"The main research is the automatic generation of micro-blog user tags based on cluster analysis. Key technologies used in this paper are introduced firstly; mainly include cluster technology and TextRank. A Baseline system is proposed in order to show the validity of the research proposed by this paper. Then the automatic generation method based on clustering analysis is illustrated detailedly. Finally analyze and evaluate the method by experiments. The experimental results show that the user tags generated by the method can solve the problem of synonymy tags stack, and the tags can reflect the users' interest in more dimensions.","PeriodicalId":6473,"journal":{"name":"2014 IEEE 5th International Conference on Software Engineering and Service Science","volume":"734 1","pages":"633-636"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 5th International Conference on Software Engineering and Service Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSESS.2014.6933648","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The main research is the automatic generation of micro-blog user tags based on cluster analysis. Key technologies used in this paper are introduced firstly; mainly include cluster technology and TextRank. A Baseline system is proposed in order to show the validity of the research proposed by this paper. Then the automatic generation method based on clustering analysis is illustrated detailedly. Finally analyze and evaluate the method by experiments. The experimental results show that the user tags generated by the method can solve the problem of synonymy tags stack, and the tags can reflect the users' interest in more dimensions.
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