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What are some of the challenges that make language hard in the context of natural language processing?
What are some of the challenges that make language hard in the context of natural language processing?
Tremendous ambiguity, variability, grounding, and sparsity are some of the challenges that make language hard in NLP.
How does Zipf's Law apply to language and what does it reveal about the distribution of words?
How does Zipf's Law apply to language and what does it reveal about the distribution of words?
Zipf's Law reveals that few words make up a great share of the text, with the second most frequent word appearing half as much as the first, the third one appearing one fourth as much, and so on.
What disciplines does NLP draw upon for its foundation?
What disciplines does NLP draw upon for its foundation?
NLP draws upon Human & Social Sciences, Linguistics, and Cognition & Neuroscience for its foundation.
How does the variability of language pose a challenge in NLP?
How does the variability of language pose a challenge in NLP?
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What role does grounding in common sense play in the challenge of learning language?
What role does grounding in common sense play in the challenge of learning language?
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What is the difference between Extractive Summarization and Abstractive Summarization?
What is the difference between Extractive Summarization and Abstractive Summarization?
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What is the objective of text normalization in NLP?
What is the objective of text normalization in NLP?
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Why are numbers and dates usually replaced by special tokens in NLP preprocessing?
Why are numbers and dates usually replaced by special tokens in NLP preprocessing?
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What is the purpose of stemming in NLP?
What is the purpose of stemming in NLP?
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How does lemmatization differ from stemming in NLP?
How does lemmatization differ from stemming in NLP?
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