Presentation 2022-12-21
Generating Student Progress Reports in Cram School Based on Keywords
Shumpei Kobashi, Tsunenori Mine,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) In many cram schools, instructors write reports on students' progress after each class. The generation of these reports is a heavy burden for instructors, and there is a need to reduce this burden. We have proposed a model that automatically generates a student learning status reports using keywords in our previous studies. However, in our previous study, there were some problems: sentences containing concrete expressions could not be generated well, and the keyword extraction method had not been sufficiently investigated. To solve these problems, we evaluated the performance of the keyword extraction methods by converting concrete expressions into tokens and comparing multiple keyword extraction methods. As a result, we obtained knowledge about keyword extraction methods and confirmed the improvement of accuracy in generating report sentences
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Sentence Generation / Cram School / Seq2Seq / Keyword Extract
Paper # AI2022-44
Date of Issue 2022-12-14 (AI)

Conference Information
Committee AI
Conference Date 2022/12/21(1days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Yuichi Sei(Univ. of Electro-Comm.)
Vice Chair Yuko Sakurai(AIST) / Tadachika Ozono(Nagoya Inst. of Tech.)
Secretary Yuko Sakurai(Tokyo Univ. of Agriculture and Technology) / Tadachika Ozono(Toho Univ.)
Assistant Kazutaka Matsuzaki(Chuo Univ.)

Paper Information
Registration To Technical Committee on Artificial Intelligence and Knowledge-Based Processing
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Generating Student Progress Reports in Cram School Based on Keywords
Sub Title (in English)
Keyword(1) Sentence Generation
Keyword(2) Cram School
Keyword(3) Seq2Seq
Keyword(4) Keyword Extract
1st Author's Name Shumpei Kobashi
1st Author's Affiliation Kyushu University(Kyushu Univ)
2nd Author's Name Tsunenori Mine
2nd Author's Affiliation Kyushu University(Kyushu Univ)
Date 2022-12-21
Paper # AI2022-44
Volume (vol) vol.122
Number (no) AI-322
Page pp.pp.62-67(AI),
#Pages 6
Date of Issue 2022-12-14 (AI)