N-gram Model

An N-gram model is a type of probabilistic language model used in natural language processing and computational linguistics. It predicts the likelihood of a sequence of words occurring together in a sentence. Think of it like predicting the next word in a text message based on the few words you’ve already typed. The ‘N’ represents the number of words considered at a time. For instance, in a bigram (2-gram) model, the model looks at two words at a time to make its predictions, like “good morning.”

In business intelligence and data analytics, N-gram models are useful for tasks like text analysis or automatic speech recognition. They can help decipher patterns in customer feedback or transcribe spoken customer service calls into text. By understanding the sequence in which words are most likely to appear, businesses can better understand the context and sentiment behind customer communications.

N-gram models are a simple yet effective way for businesses to process and analyze large amounts of text data. This helps in improving search algorithms, fine-tuning recommendation engines, or even detecting spam. By analyzing the flow of language in customer interactions, companies can gain deeper insights, improve customer engagement, and refine their marketing messages.