DocumentCode :
3637593
Title :
Finding Patterns of Students´ Behavior in Synthetic Social Networks
Author :
Gamila Obadi;Pavla Dráždilová;Jan Martinovic;Katerina Slaninová;Václav Snášel
Author_Institution :
Dept. of Comput. Sci., Tech. Univ. of Ostrava, Ostrava, Czech Republic
fYear :
2010
Firstpage :
411
Lastpage :
413
Abstract :
Spectral clustering is a data mining method used for finding patterns in high dimensional datasets. It has been applied effectively to solve many problems in signal processing, bioinformatics, etc. In this paper spectral clustering was implemented to find students’ patterns of behavior in an elearning system, to explore the relationship between the similarity of students’behavior and their academic performance.
Keywords :
"Microeconomics","Laplace equations","Eigenvalues and eigenfunctions","Social network services","Data mining","Clustering algorithms","Electronic learning"
Publisher :
ieee
Conference_Titel :
Advances in Social Networks Analysis and Mining (ASONAM), 2010 International Conference on
Print_ISBN :
978-1-4244-7787-6
Type :
conf
DOI :
10.1109/ASONAM.2010.63
Filename :
5563070
Link To Document :
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