NGD

NGD is an acronym that can refer to several different concepts depending on context. The most widely cited meaning is Normalized Google Distance, a measure used in information theory and computational linguistics to quantify semantic similarity between two terms based on web page counts.

Normalized Google Distance computes a distance between two terms by comparing the number of pages containing each term individually and the number of pages containing both terms, relative to the total number of pages indexed by the search engine. A common form is NGD(x,y) = (max(log f(x), log f(y)) - log f(x,y)) / (log N - min(log f(x), log f(y))), where f(x) is the number of pages containing x, f(x,y) is the number containing both x and y, and N is the total number of pages indexed. Lower NGD values indicate greater relatedness between the terms, while higher values indicate less similarity. The approach links to ideas in Kolmogorov complexity and information distance and has been used for tasks such as word sense disambiguation and clustering of related terms. It is noted for its simplicity and reliance on publicly accessible search results, but it also faces criticisms regarding the stability and representativeness of search engine indexes.

Beyond Normalized Google Distance, NGD serves as an acronym in various domains, including industry, organizations, and technologies. Because meanings vary by field, correct interpretation of NGD requires contextual cues from the surrounding material, such as the discipline, project name, or organizational reference.