典型文献
Incremental User Identification Across Social Networks Based on User-Guider Similarity Index
文献摘要：
Identifying accounts across different online social networks that belong to the same user has attracted extensive attentions.However,existing techniques rely on given user seeds and ignore the dynamic changes of online social networks,which fails to generate high quality identification results.In order to solve this problem,we propose an incremental user identification method based on user-guider similarity index(called CURIOUS),which efficiently identifies users and well captures the changes of user features over time.Specifically,we first construct a novel user-guider similarity index(called USI)to speed up the matching between users.Second we propose a two-phase user identification strategy consisting of USI-based bidirectional user matching and seed-based user matching,which is effective even for incomplete networks.Finally,we propose incremental maintenance for both USI and the identification results,which dynamically captures the instant states of social networks.We conduct experimental studies based on three real-world social networks.The experiments demonstrate the effectiveness and the efficiency of our proposed method in comparison with traditional methods.Compared with the traditional methods,our method improves precision,recall and rank score by an average of 0.19,0.16 and 0.09 respectively,and reduces the time cost by an average of 81％.
文献关键词：
中图分类号：
作者姓名：
Yue Kou;Dong Li;De-Rong Shen;Tie-Zheng Nie;Ge Yu
作者机构：
School of Computer Science and Engineering,Northeastern University,Shenyang 110004,China;School of Information,Liaoning University,Shenyang 110036,China
文献出处：
引用格式：
[1]Yue Kou;Dong Li;De-Rong Shen;Tie-Zheng Nie;Ge Yu-.Incremental User Identification Across Social Networks Based on User-Guider Similarity Index)[J].计算机科学技术学报（英文版）,2022(05):1086-1104
A类：
Guider,guider,CURIOUS
B类：
Incremental,User,Identification,Across,Social,Networks,Based,Similarity,Index,Identifying,accounts,across,different,online,social,networks,that,belong,same,attracted,extensive,attentions,However,existing,techniques,rely,given,seeds,ignore,changes,which,fails,generate,high,quality,identification,results,order,solve,this,problem,incremental,similarity,called,efficiently,identifies,users,well,captures,features,over,Specifically,first,construct,novel,USI,speed,up,matching,between,Second,phase,strategy,consisting,bidirectional,even,incomplete,Finally,maintenance,both,dynamically,instant,states,We,conduct,experimental,studies,three,real,world,experiments,demonstrate,effectiveness,efficiency,our,proposed,comparison,traditional,methods,Compared,improves,precision,recall,rank,score,by,average,respectively,reduces,cost
AB值：
0.527607
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