STACY: Strength of Ties Automatic-Classifier over the Years

Michele A. Brandão, Pedro O. S. Vaz de Melo, Mirella M. Moro
{"title":"STACY: Strength of Ties Automatic-Classifier over the Years","authors":"Michele A. Brandão, Pedro O. S. Vaz de Melo, Mirella M. Moro","doi":"10.5753/jidm.2018.1636","DOIUrl":null,"url":null,"abstract":"With the evolution of Web technology and its worldwide use by regular people, there is now data about not only such people but also their relations. Database research has evolved as well to tackle the myriad of problems that arrive with such volumes of data. Here, we contribute to such a trend by proposing a new algorithm (STACY) to automatically classify tie strength (an intrinsic property of relationships) considering time. We show that each class has singular and different behavior, and analyze them over co-authorship networks. Also, STACY identifies strong relationships that persist more than the ones classified by a state of the art algorithm. Finally, we derive a computational model from STACY that is able to automatically identify relationships classes with low computational cost.","PeriodicalId":301338,"journal":{"name":"J. Inf. Data Manag.","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"J. Inf. Data Manag.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5753/jidm.2018.1636","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

With the evolution of Web technology and its worldwide use by regular people, there is now data about not only such people but also their relations. Database research has evolved as well to tackle the myriad of problems that arrive with such volumes of data. Here, we contribute to such a trend by proposing a new algorithm (STACY) to automatically classify tie strength (an intrinsic property of relationships) considering time. We show that each class has singular and different behavior, and analyze them over co-authorship networks. Also, STACY identifies strong relationships that persist more than the ones classified by a state of the art algorithm. Finally, we derive a computational model from STACY that is able to automatically identify relationships classes with low computational cost.
史黛西:多年来领带自动分类器的强度
随着网络技术的发展和普通人在世界范围内的使用,现在不仅有关于这些人的数据,还有他们之间的关系。数据库研究也在不断发展,以解决海量数据带来的无数问题。在这里,我们通过提出一种新的算法(STACY)来为这种趋势做出贡献,该算法可以根据时间自动对关系强度(关系的固有属性)进行分类。我们展示了每个类都有单一和不同的行为,并在合著网络上分析了它们。此外,STACY识别出比最先进算法分类的关系更持久的强关系。最后,我们从STACY中推导出一个计算模型,该模型能够以较低的计算成本自动识别关系类。
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:604180095
Book学术官方微信