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Related Questions
- How do traditional bag-of-words models handle out-of-vocabulary words compared to word embeddings?
- What are the limitations of traditional bag-of-words in capturing contextual relationships between words?
- How do word embeddings improve the accuracy of topic modeling tasks compared to traditional bag-of-words?
- What are some common challenges in training word embeddings for topic modeling?
- Can you explain the concept of distributed representation in word embeddings and its impact on topic modeling?
- How do word embeddings handle polysemy and homophones in topic modeling?
- What is the effect of word embeddings on the interpretability of topic models compared to traditional bag-of-words?
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