An Improved Method of Reliable Content Extraction from Partially Unreliable Publications in Plural Number of Sources over the Network

Taiga Shimizu, S. Sugawara
{"title":"An Improved Method of Reliable Content Extraction from Partially Unreliable Publications in Plural Number of Sources over the Network","authors":"Taiga Shimizu, S. Sugawara","doi":"10.1109/ICIET56899.2023.10111381","DOIUrl":null,"url":null,"abstract":"This paper discusses a method of simplifying the model of information dissemination and mainly eliminating errors statistically without going into semantics for the same content collected from many information sources scattered over the network. In the methods we proposed in the past, it is assumed that the same content collected from the sources can be divided into parts that have independent values. By taking a majority vote about the value of each part, the content consisting of only the part with major values is reconstructed. For the improvement of the extraction accuracy of the reliable part of the target content, more efficient weighting ways of majority voting and their effects are discussed.","PeriodicalId":332586,"journal":{"name":"2023 11th International Conference on Information and Education Technology (ICIET)","volume":"260 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 11th International Conference on Information and Education Technology (ICIET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIET56899.2023.10111381","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

This paper discusses a method of simplifying the model of information dissemination and mainly eliminating errors statistically without going into semantics for the same content collected from many information sources scattered over the network. In the methods we proposed in the past, it is assumed that the same content collected from the sources can be divided into parts that have independent values. By taking a majority vote about the value of each part, the content consisting of only the part with major values is reconstructed. For the improvement of the extraction accuracy of the reliable part of the target content, more efficient weighting ways of majority voting and their effects are discussed.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
一种从网络上多个来源的部分不可靠出版物中提取可靠内容的改进方法
本文讨论了一种简化信息传播模型的方法,对于分散在网络上的许多信息源收集的相同内容,主要是在统计上消除错误,而不涉及语义。在我们过去提出的方法中,假设从源收集的相同内容可以分为具有独立值的部分。通过对各部分的值进行多数投票,重构出只包含主要值部分的内容。为了提高目标内容可靠部分的提取精度,讨论了更有效的多数投票加权方法及其效果。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Using Deep Learning to Track Representational Flexibility Development of Children with Autism in a Virtual World Emotional Responses toward the Flipped Classroom Approach across Academic Disciplines Assessment of Learning Outcomes in the (Java) Object-Oriented Programming Courses Human’s Reaction Time Based Score Calculation of Self-practice Dynamic Yoga System for User’s Feedback by OpenPose and Fuzzy Rules Using 360 Virtual Reality Video in History Learning
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1