DocumentCode :
2086110
Title :
Associative Language Learning Support Applying Graph Clustering For Vocabulary Learning and Improving Associative Ability
Author :
Jung, Jaeyoung ; Makoshi, Nobuyasu ; Akama, Hiroyuki
Author_Institution :
Dept. of Human Syst. Sci., Tokyo Inst. of Technol., Tokyo
fYear :
2008
fDate :
1-5 July 2008
Firstpage :
228
Lastpage :
232
Abstract :
In this study, we propose a new Web-based associative language learning system, called ALL It assumes that word association exercise and associative information about words would be useful for vocabulary learning and improving associative ability. For this, word association sources are used, and a graph theory and a graph clustering are employed as suitable tools for organizing the data structure and for mining meaningful information from it.
Keywords :
associative processing; computer aided instruction; graph theory; pattern clustering; associative ability; associative language learning support; data structure; graph clustering; graph theory; information mining; vocabulary learning; word association sources; Data structures; Databases; Graph theory; Humans; Large-scale systems; Learning systems; Organizing; Thesauri; Usability; Vocabulary; associative vocabulary learning; computer-assisted vocabulary learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Learning Technologies, 2008. ICALT '08. Eighth IEEE International Conference on
Conference_Location :
Santander, Cantabria
Print_ISBN :
978-0-7695-3167-0
Type :
conf
DOI :
10.1109/ICALT.2008.40
Filename :
4561672
Link To Document :
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