DocumentCode
2132042
Title
GRAPHITE: A Visual Query System for Large Graphs
Author
Chau, Duen Horng ; Faloutsos, Christos ; Tong, Hanghang ; Hong, Jason I. ; Gallagher, Brian ; Eliassi-Rad, Tina
fYear
2008
fDate
15-19 Dec. 2008
Firstpage
963
Lastpage
966
Abstract
We present Graphite, a system that allows the user to visually construct a query pattern, finds both its exact and approximate matching subgraphs in large attributed graphs, and visualizes the matches. For example, in a social network where a person\´s occupation is an attribute, the user can draw a \´star\´ query for "finding a CEO who has interacted with a Secretary, a Manager, and an Accountant, or a structure very similar to this". Graphite uses the G-Ray algorithm to run the query against a user-chosen data graph, gaining all of its benefits, namely its high speed, scalability, and its ability to find both exact and near matches. Therefore, for the example above, Graphite tolerates indirect paths between, say, the CEO and the Accountant, when no direct path exists. Graphite uses fast algorithms to estimate node proximities when finding matches, enabling it to scale well with the graph database size.We demonstrate Graphitepsilas usage and benefits using the DBLP author-publication graph, which consists of 356 K nodes and 1.9 M edges. A demo video of Graphite can be downloaded at http://www.cs.cmu.edu/~dchau/graphite/graphite.mov.
Keywords
data visualisation; query processing; social networking (online); G-ray algorithm; GRAPHITE; approximate matching subgraphs; large attributed graphs; query pattern; social network; user-chosen data graph; visual query system; Conferences; Data mining; Databases; Laboratories; Pattern matching; Scalability; Shape; Social network services; User interfaces; Visualization; GRAPHITE; fuzzy pattern matching; graph mining; visual query;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Mining Workshops, 2008. ICDMW '08. IEEE International Conference on
Conference_Location
Pisa
Print_ISBN
978-0-7695-3503-6
Electronic_ISBN
978-0-7695-3503-6
Type
conf
DOI
10.1109/ICDMW.2008.99
Filename
4734028
Link To Document