: NLP Vocabulary: out-of-vocabulary words

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out-of-vocabulary words

Exploring the data further one reason for the difference in impact of spelling simplification and lemma may be the rate of out-of-vocabulary words (OOV) between the texts. (Adesam & Bouma, 2016)
None of these methods can give the reader who is not familiar with the source language any information about those out-of-vocabulary (OOV) words especially when the source and target languages use different scripts. (Kashani, Joanis, Kuhn, Foster & Popowich, 2007)
Our motivation for creating such an annotation is to test the usefulness of morphological information for the Out-Of-Vocabulary word (OOV) detection a major challenge in CWS (Huang and Zhao 2007). (Ma, Kit & Gerdemann, 2012)
Some source words which cannot be translated by the translation model are called out-of-vocabulary (OOV) words. (Wang, Wang, Li, Cui & Dai, 2014)
The number of out-of-vocabulary words in Arabic is relatively significant due to its complex nature; therefore adding features and character embeddings improved the performance significantly as they compensated for the missing vectors. (Hatab, Sabty & Abdennadher, 2022)

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