An Identification Method of News Scientific Intelligence Based on TF-IDF

Lu Pan, Haibo Tang, Lei Zhou, Liuyang Wang, Quanyin Zhu
{"title":"An Identification Method of News Scientific Intelligence Based on TF-IDF","authors":"Lu Pan, Haibo Tang, Lei Zhou, Liuyang Wang, Quanyin Zhu","doi":"10.1109/DCABES.2015.131","DOIUrl":null,"url":null,"abstract":"With the development of Internet, the amount of Information has been rapidly growing which is spread widely. In order to improve the value and accuracy of science information that is pushed in this paper, an intelligence dichotomous method for science information categorization to identify science information from massive Web news is presents. During the experiment, 85.3% recognition rate of the recognition non-tech news are realized and 82.9% accuracy rate, the results show that the method can effectively identify Web science information news and reduce the amount of independent news.","PeriodicalId":444588,"journal":{"name":"2015 14th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 14th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DCABES.2015.131","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

With the development of Internet, the amount of Information has been rapidly growing which is spread widely. In order to improve the value and accuracy of science information that is pushed in this paper, an intelligence dichotomous method for science information categorization to identify science information from massive Web news is presents. During the experiment, 85.3% recognition rate of the recognition non-tech news are realized and 82.9% accuracy rate, the results show that the method can effectively identify Web science information news and reduce the amount of independent news.
基于TF-IDF的新闻科学智能识别方法
随着互联网的发展,信息的数量迅速增长,传播广泛。为了提高推送的科学信息的价值和准确性,本文提出了一种基于智能二分法的科学信息分类方法,从海量网络新闻中识别科学信息。实验中,非科技新闻的识别识别率达到了85.3%,准确率达到了82.9%,结果表明该方法能够有效地识别Web科学信息新闻,减少了独立新闻的数量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信