Title Alternative |
Proposing an Unsupervised Approach to Evaluate Essays Using IDF on Reference Data
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FullText URL |
NLC2018-33.pdf
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Author |
Ohno, Masayuki|
Takeuchi, Koichi|
Motojin, Kota|
Obata, Yuya|
Taguchi, Masahiro|
Inada, Yoshihiko|
Iizuka, Masaya|
Abo, Tatsuhiko|
Ueda, Hitoshi|
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Abstract Alternative |
In this paper, we describe an on-going study of developing an automatic essay-scoring system in Japanese. Essay scoring systems have already been developed and used mainly in English, while not many previous studies have been done on Japanese essay evaluations. Most of the methods and systems of automatic essay evaluation need not small number of previously human-graded essays for calibrating the parameter of regression functions or parameter of machine learning. The previous studies show the high performance for essay evaluation task, however, it must be not easy to assume large graded essays in, for example, actual tests or entrance examinations. Thus, we take a approach to evaluate Japanese essays without previously human-graded essays but with assuming reference data related to essay questions. The proposed method is a simple one, that is, evaluating the essays with co-occurrences with the reference data in their words or morphemes. In the method technical terms would be given high scores using neologd dictionary and idf values. Experimental results show that the proposed method works well in our developing Japanese mock trial writing tests. Key words automatic scoring of essays, human annotation, supporting
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Keywords |
自動採点 (automatic scoring of essays)
アノテーション (human annotation)
採点支援 (supporting system of essay evaluation)
idf
neologd
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Published Date |
2018-12
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Publication Title |
IEICE technical report. Natural language processing and models of communication
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Volume |
volume118
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Issue |
issue355
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Publisher |
電子情報通信学会
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Start Page |
103
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End Page |
108
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ISSN |
09135685
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NCID |
AA11524632
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Content Type |
Journal Article
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language |
日本語
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OAI-PMH Set |
岡山大学
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Copyright Holders |
copyright@2018
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File Version |
publisher
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