{"title":"Method of tags recommendation for blogs: A comparative study","authors":"Li-Juan Tang, Cheng-Zhi Zhang","doi":"10.1109/ICMLC.2012.6359689","DOIUrl":null,"url":null,"abstract":"Tags are products of Web 2.0. They play an important role in user modeling, friends or information recommendation. In this paper, keywords from blogs are extracted by using TextRank and TF*IDF algorithms respectively. The keywords are used to tag recommendation. Experiment results show that the performance of these two algorithms is very closely.","PeriodicalId":128006,"journal":{"name":"2012 International Conference on Machine Learning and Cybernetics","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Conference on Machine Learning and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMLC.2012.6359689","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Tags are products of Web 2.0. They play an important role in user modeling, friends or information recommendation. In this paper, keywords from blogs are extracted by using TextRank and TF*IDF algorithms respectively. The keywords are used to tag recommendation. Experiment results show that the performance of these two algorithms is very closely.
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