{"title":"基于 GCN 的弱监督群落检测与更新结构中心选择","authors":"Liping Deng, Bing Guo, Wen Zheng","doi":"10.1080/09540091.2023.2291995","DOIUrl":null,"url":null,"abstract":"Community detection is a classic problem in network learning. Semi-supervised network learning requires a certain amount of known samples, while sample annotation is time-consuming and laborious. I...","PeriodicalId":50629,"journal":{"name":"Connection Science","volume":null,"pages":null},"PeriodicalIF":3.2000,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"GCN-based weakly-supervised community detection with updated structure centres selection\",\"authors\":\"Liping Deng, Bing Guo, Wen Zheng\",\"doi\":\"10.1080/09540091.2023.2291995\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Community detection is a classic problem in network learning. Semi-supervised network learning requires a certain amount of known samples, while sample annotation is time-consuming and laborious. I...\",\"PeriodicalId\":50629,\"journal\":{\"name\":\"Connection Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2024-01-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Connection Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/09540091.2023.2291995\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Connection Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/09540091.2023.2291995","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
GCN-based weakly-supervised community detection with updated structure centres selection
Community detection is a classic problem in network learning. Semi-supervised network learning requires a certain amount of known samples, while sample annotation is time-consuming and laborious. I...
期刊介绍：
Connection Science is an interdisciplinary journal dedicated to exploring the convergence of the analytic and synthetic sciences, including neuroscience, computational modelling, artificial intelligence, machine learning, deep learning, Database, Big Data, quantum computing, Blockchain, Zero-Knowledge, Internet of Things, Cybersecurity, and parallel and distributed computing.
A strong focus is on the articles arising from connectionist, probabilistic, dynamical, or evolutionary approaches in aspects of Computer Science, applied applications, and systems-level computational subjects that seek to understand models in science and engineering.
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