👉 Dictionary computing, also known as dictionary-based language modeling, is a statistical approach to natural language processing that predicts the likelihood of a word appearing in a given context by examining the frequencies of words and their co-occurrences within a large corpus of text. The process involves creating a dictionary where each unique word in the corpus is represented as a node, and edges connect nodes representing adjacent words or phrases. Given a new sentence, the model calculates the probability of each word by summing the probabilities of all words that appear together according to the dictionary, effectively leveraging the statistical patterns learned from the corpus to generate predictions about word sequences. This method is foundational in tasks like text generation, machine translation, and speech recognition, where understanding context and predicting next words is crucial.
