A space efficient scheme for persistent graph representation

被引：14
|
作者：
Kontopoulos, Stavros [1 ]
Drakopoulos, Georgios [1 ]
机构：
[1] Univ Patras, Comp Engn & Informat Dept, Patras 26500, Greece
来源：
2014 IEEE 26TH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI) | 2014年
关键词：
Graphical models; Complex networks; Graph databases; Persistent graphs; Self-adjusting persistence;
D O I：
10.1109/ICTAI.2014.52
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Graph mining is currently the focus of intense research. Major driving factors include social media, opinion mining, and the schemaless noSQL databases. Time evolving or dynamic graphs are the primary data structures in these fields. Often dynamic graphs must support persistency, meaning that from any given graph state past states can be accessed. Within the graph database context, persistency enables rollback capability, whereas in social media several phenomena such as friend deletion can be modeled. A novel, efficient, and persistent data structure based on tries is proposed. Its potential is displayed by added persistency to the deterministic Kronecker graph model.
引用
收藏
页码：299 / 303
页数：5
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