Presentation 2022-12-21
Error analysis based on Authorship Attribution results from employee training review texts
Kanta Takeuchi, Tsunenori Mine,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) This study proposes Authorship Attribution method based on the reflection texts as one of the analyses of the reflection texts. We also constructed a network using the Authorship Attribution results as an error analysis, and analyzed the effectiveness of the proposed method. The effectiveness of the proposed method was verified and analyzed.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Modality / BERT / Author Attribution
Paper # AI2022-38
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)
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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) Error analysis based on Authorship Attribution results from employee training review texts
Sub Title (in English)
Keyword(1) Modality
Keyword(2) BERT
Keyword(3) Author Attribution
1st Author's Name Kanta Takeuchi
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 # AI2022-38
Volume (vol) vol.122
Number (no) AI-322
Page pp.pp.30-35(AI),
#Pages 6
Date of Issue 2022-12-14 (AI)