DocumentCode :
3134635
Title :
Homology graph mining for social network analysis
Author :
Gaol, Ford Lumban
Author_Institution :
Dept. of Grad. Program in Comput. Sci., Bina Nusantara Univ., Jakarta, Indonesia
fYear :
2011
fDate :
27-29 Dec. 2011
Firstpage :
269
Lastpage :
272
Abstract :
In this paper, we present a methodology, called Homology Graph Mining, for computer-aided extraction of Social Network rules from consolidated homology graphs of statements. First, we will generate homology sources of a set of heterogeneous social networks resources in terms of relevant pathway. Second, combine a homology graph by means of homology integration of the social network resources. Third, Search and Analyze patterns from the graph. Fourth, generate and evaluate a set of candidate social network rules, which are maintained and indexed for interactive discovery of actionable rules. As part of implementation efforts of the methodology, framework architecture of specialized interrelated knowledge discovery services is proposed, and an application in biomedicine is initiated.
Keywords :
data mining; graph theory; medical computing; social networking (online); biomedicine; computer aided social network rules extraction; homology graph mining; interactive actionable rules discovery; social network analysis; Grammar; Navigation; OWL; Ontologies; World Wide Web; Graph Mining; Homology; Social Networks; interrelated knowledge discovery;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
e-Education, Entertainment and e-Management (ICEEE), 2011 International Conference on
Conference_Location :
Bali
Print_ISBN :
978-1-4577-1381-1
Type :
conf
DOI :
10.1109/ICeEEM.2011.6137803
Filename :
6137803
Link To Document :
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