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Word2vec Skip-Gram Dimensionality Selection
- Subjects: Computer Science, Information Systems
- |
- Contributors:
- Kenji Yamanishi ,
- Pham Hung
03:31
13:18
04:36
Playlist
03:31
13:18
04:36
- model selection
- information criteria
- minimum description length
Video Introduction
This video is adapted from 10.3390/e23080997
In recent years, word2vec has been widely applied to many aspects of Natural Language Processing (NLP) and information retrieval such as machine translation, text classification, text summarization, and named entity recognition. Furthermore, word2vec is used in various fields such as materials science, healthcare, and recommendation engines.
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Cite
If you have any further questions, please contact Encyclopedia Editorial Office.
Yamanishi, K.; Hung, P. Word2vec Skip-Gram Dimensionality Selection. Encyclopedia. Available online: https://encyclopedia.pub/video/353 (accessed on 09 June 2026).
Yamanishi K, Hung P. Word2vec Skip-Gram Dimensionality Selection. Encyclopedia. Available at: https://encyclopedia.pub/video/353. Accessed June 09, 2026.
Yamanishi, Kenji, Pham Hung. "Word2vec Skip-Gram Dimensionality Selection" Encyclopedia, https://encyclopedia.pub/video/353 (accessed June 09, 2026).
Yamanishi, K., & Hung, P. (2022, June 28). Word2vec Skip-Gram Dimensionality Selection. In Encyclopedia. https://encyclopedia.pub/video/353
Yamanishi, Kenji and Pham Hung. "Word2vec Skip-Gram Dimensionality Selection." Encyclopedia. Web. 28 June, 2022.
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