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Related Questions
- What is the impact of using word embeddings on out-of-vocabulary (OOV) words in natural language processing?
- How do Word2Vec and GloVe handle OOV words, and what are the implications for NLP pipelines?
- Can you explain how word embeddings mitigate the OOV problem, and what are the benefits of using them?
- What are some common techniques used to handle OOV words in NLP, and how do word embeddings fit into these strategies?
- How do the dimensions of word embeddings affect their ability to handle OOV words, and what are some best practices for choosing dimensionality?
- What is the relationship between word embeddings and the concept of polysemy, and how do they impact OOV word handling?
- Can you compare and contrast the OOV handling capabilities of Word2Vec and GloVe, and what are the implications for NLP pipeline design?
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