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Related Questions
- How do word embeddings like Word2Vec and GloVe handle words that are not present in their training data?
- What are the common strategies used by word embeddings to handle out-of-vocabulary (OOV) words?
- How do word embeddings affect the performance of text classification tasks when encountering OOV words?
- Can you explain the concept of subword modeling and how it relates to handling OOV words in word embeddings?
- What are some implications of using word embeddings that rely on subword modeling for text analysis tasks?
- How do word embeddings with subword modeling impact the performance of named entity recognition (NER) tasks?
- What are some potential limitations of using word embeddings to handle OOV words in text analysis tasks?
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