Title Alternative Proposing an Unsupervised Approach to Evaluate Essays Using IDF on Reference Data
FullText URL NLC2018-33.pdf
Author Ohno, Masayuki| Takeuchi, Koichi| Motojin, Kota| Obata, Yuya| Taguchi, Masahiro| Inada, Yoshihiko| Iizuka, Masaya| Abo, Tatsuhiko| Ueda, Hitoshi|
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
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
Published Date 2018-12
Publication Title IEICE technical report. Natural language processing and models of communication
Volume volume118
Issue issue355
Publisher 電子情報通信学会
Start Page 103
End Page 108
ISSN 09135685
NCID AA11524632
Content Type Journal Article
language 日本語
OAI-PMH Set 岡山大学
Copyright Holders copyright@2018
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