| Item type |
学術雑誌論文 / Journal Article(1) |
| 公開日 |
2023-07-31 |
| タイトル |
|
|
タイトル |
Infinite SCAN: An Infinite Model of Diachronic Semantic Change |
|
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 |
| アクセス権 |
|
|
アクセス権 |
metadata only access |
|
アクセス権URI |
http://purl.org/coar/access_right/c_14cb |
| 著者 |
Inoue, Seiichi
Komachi, Mamoru
Ogiso, Toshinobu
Takamura, Hiroya
Mochihashi, Daichi
|
| 著者所属(英) |
|
|
内容記述タイプ |
Other |
|
内容記述 |
Tokyo Metropolitan University |
|
言語 |
en |
| 著者所属(英) |
|
|
内容記述タイプ |
Other |
|
内容記述 |
Tokyo Metropolitan University |
|
言語 |
en |
| 著者所属(英) |
|
|
内容記述タイプ |
Other |
|
内容記述 |
The National Institute for Japanese Language and Linguistics |
|
言語 |
en |
| 著者所属(英) |
|
|
内容記述タイプ |
Other |
|
内容記述 |
The National Institute of Advanced Industrial Science and Technology |
|
言語 |
en |
| 著者所属(英) |
|
|
内容記述タイプ |
Other |
|
内容記述 |
The Institute of Statistical Mathematics |
|
言語 |
en |
| 抄録(英) |
|
|
内容記述タイプ |
Abstract |
|
内容記述 |
In this study, we propose a Bayesian model that can jointly estimate the number of senses of words and their changes through time.The model combines a dynamic topic model on Gaussian Markov random fields with a logistic stick-breaking process that realizes Dirichlet process. In the experiments, we evaluated the proposed model in terms of interpretability, accuracy in estimating the number of senses, and tracking their changes using both artificial data and real data.We quantitatively verified that the model behaves as expected through evaluation using artificial data.Using the CCOHA corpus, we showed that our model outperforms the baseline model and investigated the semantic changes of several well-known target words. |
|
言語 |
en |
| 出版者 |
|
|
出版者 |
Association for Computational Linguistics |
| 書誌情報 |
en : Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
巻 2022,
p. 1605-1616,
ページ数 12,
発行日 2022-12
|
| 関連サイト |
|
|
|
識別子タイプ |
URI |
|
|
関連識別子 |
https://aclanthology.org/2022.emnlp-main.104/ |
