👉 Dice computing is a metric used to evaluate the similarity between two text documents, typically by measuring the overlap in their vocabulary. It operates on the principle that if a document shares more words with another than would be expected by chance, the two documents are likely more similar. The computation involves creating a set of terms (words or phrases) from each document and then calculating the intersection of these sets, often using a simple formula like (intersection size / union size). The Dice coefficient is then derived by dividing the intersection size by the product of the sizes of the two sets, resulting in a value between 0 and 1, where 1 indicates perfect similarity. This approach is particularly useful in natural language processing tasks such as information retrieval, text classification, and summarization, where understanding the semantic relationship between texts is crucial.
