DocumentCode
3637593
Title
Finding Patterns of Students´ Behavior in Synthetic Social Networks
Author
Gamila Obadi;Pavla Drádilová;Jan Martinovic;Katerina Slaninová;Václav Snáel
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