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Explore the acquisition of lexical knowledge from N-grams in this comprehensive lecture delivered at the Johns Hopkins University Summer School on Human Language Technology. Learn advanced techniques for extracting meaningful linguistic patterns and vocabulary information from statistical N-gram models, examining how computational methods can automatically derive lexical knowledge from large text corpora. Discover the theoretical foundations and practical applications of N-gram-based approaches to natural language processing, including methods for identifying semantic relationships, syntactic patterns, and lexical associations. Gain insights into the challenges and opportunities in automated lexical acquisition, understanding how N-gram statistics can inform dictionary construction, semantic analysis, and language modeling tasks. Examine case studies and experimental results that demonstrate the effectiveness of N-gram-based lexical knowledge extraction across different languages and domains.
