DocumentCode :
3130434
Title :
NetDriller: A Powerful Social Network Analysis Tool
Author :
Koochakzadeh, Negar ; Sarraf, Atieh ; Kianmehr, Keivan ; Rokne, Jon ; Alhajj, Reda
Author_Institution :
Dept. of Comput. Sci., Univ. of Calgary, Calgary, AB, Canada
fYear :
2011
fDate :
11-11 Dec. 2011
Firstpage :
1235
Lastpage :
1238
Abstract :
The social network methodology has gained considerable attention recently. The main motivation is to construct and analyze social networks that involve actors from a specific application domain. The advanced computing technology has facilitated automating the process and provided flexibility, robustness and scalability. A large number of automated tools exist. Each tool supports specific functions in addition to the general common functions inspired from the social network methodology. After identifying some of the interesting functions lacking in the existing tools, we have developed Net Driller as a powerful tool with distinguished capabilities. Compared to the existing tools, Net Driller supports some unique tasks, such as network construction based on data analysis by mining the raw dataset to produce more informative links between actors. Net Driller also facilitates fuzzy search on network metrics. In this demo paper, we introduce the basic features of Net Driller by focusing on the two functionalities mentioned above.
Keywords :
data analysis; data mining; social networking (online); NetDriller tool; data analysis; dataset mining; social network analysis tool; social network methodology; Clustering algorithms; Data mining; Educational institutions; Fuzzy sets; Itemsets; Measurement; Social network services; Data Mining; Fuzzy Logic; Social Network Analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Mining Workshops (ICDMW), 2011 IEEE 11th International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4673-0005-6
Type :
conf
DOI :
10.1109/ICDMW.2011.128
Filename :
6137526
Link To Document :
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