Tokenization and Stemming in Natural Language Processing

In natural language processing, the first step is to tokenize sentences by separating words and punctuation. The key is to understand the meaning behind different word forms like 'run,' 'running,' and 'ran.' Statistical approaches treat these forms as the same to capture their frequency in texts. Stemming algorithms are used to remove word conjugation, grouping similar words together. By treating sequences of words as concepts, like engrams, a deeper understanding of language can be achieved.