@article{oai:ipsj.ixsq.nii.ac.jp:00216343,
 author = {白井, 圭佑 and 松崎, 真里 and 森, 信介 and 後藤, 真 and Keisuke, Shirai and Masato, Matsuzaki and Shinsuke, Mori and Makoto, Goto},
 issue = {2},
 journal = {情報処理学会論文誌},
 month = {Feb},
 note = {人名辞典等人文学に関わる辞書類からの知識抽出は，それらを用いて人文学研究のための基盤を構築することが可能になるという点で意義がある．一方で，人手による抽出作業は場合によっては高コストになりうる．そこで，本研究では機械学習手法を用いた自動抽出器の構築を試みる．実験結果から，固有表現認識器を用いた芳賀日本人名辞典からの知識抽出では，全体的に高い抽出精度が実現可能であることが分かった．, Extracting knowledge from dictionaries like biographical ones is beneficial as they enable us to build a foundation for digital humanities research. However, knowledge extraction from dictionaries by human effort can be costly on large-scale dictionaries. To alleviate this, we developed a method for automatic knowledge extraction and tested it on a biographical dictionary. From experimental results, we found that a named entity recognizer can achieve high accuracy on a Japanese biographical dictionary.},
 pages = {293--301},
 title = {人名辞典からの知識抽出},
 volume = {63},
 year = {2022}
}