{"title":"链接预测研究进展综述","authors":"Jiahao Li, Linlan Liu, Jian Shu","doi":"10.1145/3581807.3581903","DOIUrl":null,"url":null,"abstract":"Link prediction is a technique to forecast future new or missing relationships between entities based on the current dynamic network information. After a brief introduction of the standard problem and evaluation metrics of link prediction, this review will summarize representative progresses about matrix factorization, probabilistic models, network embedding, deep learning, and some others, mainly extracted from related publications in the last decade. Finally, this review will outline some long-standing challenges for future studies.","PeriodicalId":292813,"journal":{"name":"Proceedings of the 2022 11th International Conference on Computing and Pattern Recognition","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Progresses in Link Prediction: A Survey\",\"authors\":\"Jiahao Li, Linlan Liu, Jian Shu\",\"doi\":\"10.1145/3581807.3581903\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Link prediction is a technique to forecast future new or missing relationships between entities based on the current dynamic network information. After a brief introduction of the standard problem and evaluation metrics of link prediction, this review will summarize representative progresses about matrix factorization, probabilistic models, network embedding, deep learning, and some others, mainly extracted from related publications in the last decade. Finally, this review will outline some long-standing challenges for future studies.\",\"PeriodicalId\":292813,\"journal\":{\"name\":\"Proceedings of the 2022 11th International Conference on Computing and Pattern Recognition\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2022 11th International Conference on Computing and Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3581807.3581903\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2022 11th International Conference on Computing and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3581807.3581903","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Link prediction is a technique to forecast future new or missing relationships between entities based on the current dynamic network information. After a brief introduction of the standard problem and evaluation metrics of link prediction, this review will summarize representative progresses about matrix factorization, probabilistic models, network embedding, deep learning, and some others, mainly extracted from related publications in the last decade. Finally, this review will outline some long-standing challenges for future studies.