A Space Efficient Scheme for Persistent Graph Representation

Author

Kontopoulos, Stavros ; Drakopoulos, Georgios

Author_Institution

Comput. Eng. & Inf. Dept., Univ. of Patras, Patras, Greece

fYear

2014

fDate

10-12 Nov. 2014

Firstpage

299

Lastpage

303

Abstract

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.

Keywords

data mining; persistent objects; tree data structures; trees (mathematics); deterministic Kronecker graph model; dynamic graph; friend deletion; graph database; graph mining; graph state; opinion mining; persistent data structure; persistent graph representation; rollback capability; schemaless noSQL database; social media; space efficient scheme; time evolving graph; tries; Biological system modeling; Communities; Data structures; Databases; Encoding; History; Media; Complex networks; Graph databases; Graphical models; Persistent graphs; Self-adjusting persistence;

fLanguage

English

Publisher

ieee

Conference_Titel

Tools with Artificial Intelligence (ICTAI), 2014 IEEE 26th International Conference on

Conference_Location

Limassol

ISSN

1082-3409

Type

conf

DOI

10.1109/ICTAI.2014.52

Filename

6984488