{“状态”:“确定”,“消息类型”:“工作”,“信息版本”:“1.0.0”,“讯息”:{“索引”:{“日期部分”:[[2024,7,22]],“日期时间”:“2024-07-22T18:38:47Z”,“时间戳”:1721673527064},“参考计数”:48,“出版商”:“电气与电子工程师学会(IEEE)”,“发行”:“12”,“许可证”:[{“开始”:{-“日期部分“:[2019,12,1]],”日期时间“:“2019-12-01T00:00:00Z”,“timestamp”:157515840000},“content-version”:“vor”,“delay-in-days”:0,“URL”:“https:\/\/ieeexplore.iee.org\/Xplorehelp\/downloads\/license-information\/ieee.html”},{“start”:{“date-parts”:[2019,12,1]],“date-time”:“2019-12-01T00:00 Z”,”timestamp“15751584000000}”,“content-version”:“stm-as”f“,”delay-in-days“:0,”URL“:“https:\/\/doi.org\/10.15223\/policy-029”},{“start”:{“date-parts”:[[2019,12,1]],“date-time”:“2019-12-01T00:00:00Z”,“timestamp”:157515840000},“content-version”:“stm-asf”,“delay-in-days”:0,“URL”:“http:\/\/doi.org\/10.15223\/policy-037”}],“funder”:[{“doi”:“10.13039\/501 100001809”,“名称”:“国家自然科学基金”,“doi-asserted-by”:“publisher”,“adward”:[“U1701262”,“61527812”],“id”:[{“id”:“10.13039\/501100001809”,“id type”:“doi”,“asserted by”:“publisher”}]},{“name”:“国家科技重大项目”,“award”:[”2016ZX01038101“]}”,{”name“中国工信部IT基金(TCN关键技术研究与应用)”}:“国家关键技术研发计划”,“奖项”:[“2015BAG14B01-02”]}],“内容域”:{“域”:[],“交叉标记-限制”:false},“短容器-标签”:[”IEEE Trans.Ind.Electron.“],“published-print”:{“date-parts”:[[2019,12]]},”DOI“:”10.1109\/tie.2019.2907441“,”type“:”journal-article“,”created“:{”date-part“:[2019,6,25”]],“日期-时间”:“2019-06-25T21:45:20Z”,“timestamp”:1561499120000},“page”:“9682-9691”,“source”:”Crossref“,”is-referenced-by-count“:10,“title”:[“Exploring High-Order Correlations for Industry Anomaly Detection”],“prefix”:“10.1109”,“volume”:揬66擞“:”王“,“sequence”:“first”,“affiliation”:[]},{“ORCID”:“http://\/ORCID.org\/0000-0001-7329-6461”,“authenticated-ORCID”:false,“给定”:“Zizhao”,“family”:“张”,“se序列”:“additional”,“从属关系”:[]},}“ORCID”:“:”附加“,”从属“:[]},{“given”:“Quan”,“family”:“Miao”,“sequence”:“additional”,“affiliation”:[]},{“ORCID”:”http://\/ORCID.org\/0000-0001-9163-2932“,”authenticated-ORCID“:false,”given“:”Rongrong“,”family“:”Ji“,”sequence“:”additional:“越”,“家”:“高”,“序列”:“additional”,“affiliation”:[]}],“member”:“263”,“reference”:[{“key”:“ref39”,“doi-asserted-by”:“publisher”,“doi”:“10.1109\/ICDM.2008.17”},{“key”:”ref38“,”doi-assert-by“:”publisher“,”doi“:”10.1145\/3133956.3138825 ACCESS.2018.2805845“},{”key“:”ref32“,”doi-asserted-by“:”publisher“,”doi“:“10.1109 \/ACCESS.2018.2806420”},{“key”:“ref31”,“doi-asserted-by”:“publisher”,“doi”:“10.109\/TIE.2017.2748052”}卷:“1”,“作者”:“plessis”,“年份”:“2014”,“期刊标题”:“Adv Neural Inf Process Syst”},{“key”:“ref36”,“doi asserted by”:“publisher”,“doi”:“10.24963\/ijcai.2018\/466”},{“key”:“ref35”,“首页”:“2843”,“文章标题”:“一种用于异常检测的高效半监督SVM”,“作者”:“蒙太奇”,“年份”:“0”,“期刊标题”:“Proc Int Joint Conf Neural Netw”},{“key”:“ref34”,“首页”:“1386”,“article-title”:“从正数据和未标记数据学习的凸公式”,“author”:“plessis”,“year”:“0”,“journal-title“:”Proc Int Conf Mach Learn“},{“key”:“ref10”,“doi-asserted-by”:“publisher”,“doi”:“10.1109\/TIE.2017.2726961”},“key“:”ref40“,”author“:”preiss“,“year:”1999“,”journal-title“:“Java中具有面向对象设计模式的数据结构和算法”},{“key”:“ref11”,“doi-asserted-by”:“publisher”,“doi”:“10.1109\/TIE.2016.2541087”},{“键”:“参考14”,“doi-asserted-by”:“publisher”,“doi”:“10.1145\/3178876.3185996”},{“key”:“ref15”,“doo-asserted-by”:”publisher“,”doi“:”10.1007\/978-3319-57454-7_59“},“key“:”ref16“,”first page“:“20”,“article-title”:“高效的顶级优化,使用梯度增强进行监督异常检测”,“author”:“fr\u00e9ry”,“year”:“0”,“journal-title“:“Proc-Eur-Conf Mach Learn Knowl Discovery Databases”},{“key”:“ref17”,“doi-asserted-by”:“publisher”,“doi”:“10.1109\/IJCNN.2016.7727554”}、{“密钥”:“ref18”,“doi-asserte-by”:“publisher”、“doi“:”10.1145\/2806890“},}“key:”ref19“article-title”:“Olivier Chapelle、Bernhard Schölkopf和Alexander Zien(审查)“,”卷“:”20“,“author”:“thomas”,“year”:“2009”,“journal-title”:“IEEE Trans Neural Netw”},{“key”:“ref28”,“doi-asserted-by”:“publisher”,”doi“:”10.1007\/978-3642-33885-4_35“},”{“key”:”ref4“,”doi-assert-by“:”publisher doi“:”10.1007\/978-3642-15549-9_27“},{“键”:“参考3”,“doi断言者”:“publisher”,“doi”:“10.1109\/IJCNN.2005.156431”},{“key”:“ref6”,“doi断言者”:“publisher”,“doi”:“10.1109\/ICDM.2011.152”},{“key”:“ref29”,“doi断言者”:“publisher”,“doi”:“10.1109\/TGRS.2018.289692”},{“key”:“ref5”,“doi断言者”:“publisher”,“doi”:“10.1109\/ICDM.2017..27“},{”key“:”ref8“,”doi断言者“:”publisher“,”doi“:“10.1109\/TII.2017.2772082”},{“key”:“ref7”,“doi-asserted-by”:“publisher”,“doi”:“10.109\/ICDM.2016.0119”}、{“key”:”ref2“,”doi-assert-by“:”publisher“,”doi“:”10.1109\/TPAMI.2018.2875002},{“key”:“ref1”,“doi-asserted-by”:“publisher”,“doi”:“10.1109\/TIE.2017.2772190”},{“key”:“ref46”,“first-page”:“449”,“author”:“yeh”,“year”:“2009”,“journal-title”:“通过过采样主成分分析进行异常检测”},{“key”:”ref20“,”first-page:“27”,“article-title“:”semi-ministed clustering by semi-missued“,”author“:”basu“,”year“:”0“”:“publisher”,“DOI”:“10.1145\/2133360.2133363”},{“key”:“ref48”,“DOI-asserted-by”:“publicher”,“DOI”:”10.24963\/ijcai.2017\/387“},“{”key“:”ref22“,”DOI-assert-by“:”publisher“,”DOI“:”10.1109\/SP.2010.25“}预测”,“体积”:“24”,“author”:“zhang”,“year”:“2016”,“journal-title”:“Automated Softw Eng”},{“key”:“ref21”,“article-title“:“Ganomaly:通过对抗训练进行半监督异常检测”,“author”:“akcay”,“年”:“2018”,“日记标题”:“CoRR”}“物品标签”:“超图学习:聚类、分类和嵌入”,“author”:“sch\u00f6lkopf”,“year”:“0”,“journal-title”:“Proc-Int Conf Neural Inf Process”},{“key”:“ref41”,“article-title“:”UCI机器学习库“,”author“:”dheeru“,”year“:”2017},{“键”:“ref44”,“doi-asserted-by”:“publisher”,“doi”:“10.1137\/17M1121184”},{“key”:“ref26”,“doi-assertd-by”:“publisher”,“DI:”10.1080\/08839514.2012.629540“},”{“密钥”:“ref43”,“article-title”:“经验软件工程数据的承诺库”,“年份”:“2015”}:“10.1016\/j.cviu.2011.09.006”}],“container-title”:[“IEEE Transactions on Industrial Electronics”],“原始标题”:[],“链接”:[{“URL”:“http://\/xplorestaging.IEEE.org\/ielx7\/41\/8784422\/086844782.pdf?arnumber=8684782”,“内容类型”:“未指定”,“content-version”:“vor”,“intended-application”:“相似性检查”}],“存放”:{“日期段”:[2022,7,13]],“date-time“”:“2022-07-13T21:09:06Z”,“timestamp”:1657746546000},“score”:1,“resource”:{“primary”:{“URL”:“https:\/\/ieeexplore.iee.org\/document\/8684782\/”}},”subtitle“:[],”shorttitle“:[],”issued“:{”date-parts“:[2019,12]},‘references-count’:48,‘journal-issue’:{‘issue’:“12”},《URL》:“http”:\/\/dx.doi.org\/10.109\/tie.2019.2907441“,”关系“:{},”ISSN“:[“0278-0046”,“1557-9948”],“issn-type”:[{“value”:“0278-0046”,“type”:“print”},{“value”:“1557-9968”,“type”:“electronic”}],“subject”:[],“published”:{“date-parts”:[[2019,12]]}}}