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Word Familiarity Rate Estimation Using a Bayesian Linear Mixed Model
https://repository.ninjal.ac.jp/records/2554
https://repository.ninjal.ac.jp/records/25547bfdd827-3da1-4c71-98c1-15488ae09496
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
D19-5902.pdf (402.8 kB)
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| Item type | 学術雑誌論文 / Journal Article(1) | |||||
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| 公開日 | 2019-12-21 | |||||
| タイトル | ||||||
| タイトル | Word Familiarity Rate Estimation Using a Bayesian Linear Mixed Model | |||||
| 言語 | en | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
| 資源タイプ | journal article | |||||
| 著者 |
Asahara, Masayuki
× Asahara, Masayuki |
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| 著者所属(英) | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | National Institute for Japanese Language and Linguistics | |||||
| 抄録(英) | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | This paper presents research on word familiarity rate estimation using the 'Word List by Semantic Principles'. We collected rating information on 96,557 words in the 'Word List by Semantic Principles' via Yahoo! crowdsourcing . We asked 3,392 subject participants to use their introspection to rate the familiarity of words based on the five perspectives of 'KNOW', 'WRITE', 'READ', 'SPEAK', and 'LISTEN', and each word was rated by at least 16 subject participants. We used Bayesian linear mixed models to estimate the word familiarity rates. We also explored the ratings with the semantic labels used in the 'Word List by Semantic Principles'. | |||||
| 出版者 | ||||||
| 出版者 | Association for Computational Linguistics | |||||
| 書誌情報 |
Proceedings of the First Workshop on Aggregating and Analysing Crowdsourced Annotations for NLP p. 6-14, 発行日 2019-11 |
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| DOI | ||||||
| 関連タイプ | isIdenticalTo | |||||
| 識別子タイプ | DOI | |||||
| 関連識別子 | 10.18653/v1/D19-5902 | |||||
| フォーマット | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | application/pdf | |||||
| 著者版フラグ | ||||||
| 出版タイプ | VoR | |||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
