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Related Questions
- How do word embeddings capture semantic relationships between words?
- Can you explain the role of vector similarity in entity categorization?
- How do pre-trained word embeddings, such as Word2Vec or GloVe, improve entity categorization tasks?
- What are the key differences between vector similarity measures, such as cosine similarity and Euclidean distance?
- How do word embeddings handle out-of-vocabulary words and rare entities in entity categorization?
- Can you discuss the impact of word embedding dimensionality on entity categorization performance?
- How do word embeddings incorporate context and syntax in entity categorization tasks?
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