Presentation 2000/4/20
A Document Classification Using Feature Vectors Based on Teaching Guideline for Educational Information on the Web
Minoru NAKAYAMA, Yasutaka SHIMIZU,
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Abstract(in English) To categorize Web information as educational material, the relationships between subjects and terms that appeared in the teaching guidelines were analyzed by using the Singular Value Decomposition method, and feature vectors were extracted.The percentage corrects for classification of teaching schemes were higher in science and several subjects by using the dot-production of feature vectors.The Web information as educational or general material were also classified to a subject and grade in the same way.The degree of containing rate for dictionary terms and similarity to the subjects were compared among web documents.Codebook vectors, that were learned by a Self-Organizing Algorithm with feature vectors, then put the terms and subjects into a 2-dimensional map that described their relationship.It was examined that a Self-Organizing Map could be used for classification of Web information to the subject and grade.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) educational information / WWW / SVD / SOM / teaching guideline
Paper # ET2000-5
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Committee ET
Conference Date 2000/4/20(1days)
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Registration To Educational Technology (ET)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Document Classification Using Feature Vectors Based on Teaching Guideline for Educational Information on the Web
Sub Title (in English)
Keyword(1) educational information
Keyword(2) WWW
Keyword(3) SVD
Keyword(4) SOM
Keyword(5) teaching guideline
1st Author's Name Minoru NAKAYAMA
1st Author's Affiliation The Center for Research and Development of Educational Technology()
2nd Author's Name Yasutaka SHIMIZU
2nd Author's Affiliation Graduate School of Decision Science and Technology Tokyo Institute of Technology
Date 2000/4/20
Paper # ET2000-5
Volume (vol) vol.100
Number (no) 11
Page pp.pp.-
#Pages 8
Date of Issue