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RESEARCH ON KEY WORDS SYSTEMATIZATION FOR INFORMATION RETRIEVAL OF EDUCATIONAL RESOURCE ON THE INTERNET

RESEARCH ON KEY WORDS SYSTEMATIZATION FOR INFORMATION RETRIEVAL OF EDUCATIONAL RESOURCE ON THE INTERNET
网络教育资源信息检索关键词系统化研究
批准号:
11680210
负责人:
NAKAYAMA Minoru
金额:
$2.18万
依托单位国家:
日本
项目类别:
Grant-in-Aid for Scientific Research (C)
财政年份:
1999
资助国家:
日本
项目状态:
已结题
起止时间:
1999 至 2000

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中文摘要
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英文摘要
The aim of this research is to efficient categorization of Internet information for school teaching. This thesis conducts categorizing websites to subjects-units, based on the analysis of term-frequencies in teaching textbooks.A term-document matrix is generated by extracting terms from unit-documents with morphological analysis and summarizing terms' frequency. Each element of this matrix is the frequency of every term in every class unit. Methods to extract feature vectors of terms and documents from the adjusted matrix using SVD (Singular Value Decomposition), and to composite feature vectors of arbitrary documents from the terms' vectors are established. A suitable class-unit for the document is estimated based on the similarity of these feature vectors.A test-collection including over 120 websites, each of which has an answer made by high-school teachers, was used for the evaluation. Parameters and variables in the procedures, such as, which word classes to use, how to adjust the … More term-document matrix, the dimension size of feature vectors, etc. were optimized based on this evaluation. Results were given as a list of unit-titles in descending order of similarity between the site's feature vector and the units' vectors.To illustrate the structure of websites, SOM (Self Organizing Map), which is a kind of a non-supervised neural network learning, is used. As a result, the textbook concept space was visualized, and mapping every page that constructs an arbitrary site showed how the site-pages were distributed in this space. The validity of this map is also discussed and guidelines in reading these maps are shown.In conclusion, a document classification specialized to educational information was done. Methods to extract feature vectors from descriptions in textbooks and to composite vectors of arbitrary documents are established. Matching class-units of the document is acquired by comparing similarities between the feature vectors. Visualization of categorizing results and website-structures are also done using SOM.It is shown that using these methods, categorization and visualization of websites or documents is feasible. Less
期刊论文(8)
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会议论文
森本容介,中山実,清水康敬: "学習用Web情報の検索支援システムの開発と評価"教育工学関連学協会連合第6回全国大会. K3B38n1. 535-538 (2000)
Yosuke Morimoto、Minoru Nakayama、Yasutaka Shimizu:“学习网络信息搜索支持系统的开发和评估”第六届全国教育技术协会会议 K3B38n1(2000 年)。
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吉田直人,中山実,清水康敬: "効果的な文章表現に関する検討と文章改善支援ツールの開発"電子情報通信学会技術報告. ET99-98. 23-30 (2000)
Naoto Yoshida、Minoru Nakayama、Yasutaka Shimizu:“有效写作表达的研究和写作改进支持工具的开发”IEICE 技术报告 23-30 (2000)。
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中山実,實松北斗,清水康敬: "学習指導要領に基づいた学習情報のキーワード検索のための用語辞書に関する検討"電子情報通信学会論文誌. Vol.J83-D-I. 225-233 (2000)
Minoru Nakayama、Hokuto Sanamatsu、Yasutaka Shimizu:“基于课程指南的学习信息关键字搜索的术语词典的研究”,电子信息与通信工程师学会学报 J83-D-I. )
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中山実, 清水康敬: "用語辞書の自己組織化マップを用いた学習用Web情報の分類に関する検討"第2回自己組織化マップ(SOM)研究会講演論文集. 55-60 (2001)
Minoru Nakayama、Yasutaka Shimizu:“使用术语词典自组织映射对学习网络信息进行分类的研究”第二届自组织映射 (SOM) 研究小组论文集 55-60 (2001)。
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