{"title":"一种利用社交网络中各种特征进行链接预测的新方法","authors":"Yu Zhang, Kening Gao, Feng Li, Ge Yu","doi":"10.1109/WISA.2014.34","DOIUrl":null,"url":null,"abstract":"Link prediction is a basic problem in the research of social networks. At present, most link prediction algorithms are based on the features extracted from network structure, few research concerns the effect of natural attributes of nodes for creating a link. In this paper we develop a novel way to predict links based on Random Walk algorithm using the information from both the network topology and rich node attributes. The experiment result show that our method can help improves the prediction accuracy and it proves that node attributes have a real effect on link creation.","PeriodicalId":366169,"journal":{"name":"2014 11th Web Information System and Application Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"A New Method for Link Prediction Using Various Features in Social Networks\",\"authors\":\"Yu Zhang, Kening Gao, Feng Li, Ge Yu\",\"doi\":\"10.1109/WISA.2014.34\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Link prediction is a basic problem in the research of social networks. At present, most link prediction algorithms are based on the features extracted from network structure, few research concerns the effect of natural attributes of nodes for creating a link. In this paper we develop a novel way to predict links based on Random Walk algorithm using the information from both the network topology and rich node attributes. The experiment result show that our method can help improves the prediction accuracy and it proves that node attributes have a real effect on link creation.\",\"PeriodicalId\":366169,\"journal\":{\"name\":\"2014 11th Web Information System and Application Conference\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 11th Web Information System and Application Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WISA.2014.34\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 11th Web Information System and Application Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WISA.2014.34","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A New Method for Link Prediction Using Various Features in Social Networks
Link prediction is a basic problem in the research of social networks. At present, most link prediction algorithms are based on the features extracted from network structure, few research concerns the effect of natural attributes of nodes for creating a link. In this paper we develop a novel way to predict links based on Random Walk algorithm using the information from both the network topology and rich node attributes. The experiment result show that our method can help improves the prediction accuracy and it proves that node attributes have a real effect on link creation.