For example, in a text database, the vector might have dimensions corresponding to the frequency of each word in the vocabulary, the part of speech (noun, verb, adjective, etc.) of each word, and the sentiment (positive, negative, neutral) of each word. The resulting vector might look something like this:

[0.2, 0.1, 0.05, 0.01, 0.8, 0.3, 0.1, 0.2, 0.1, 0.05]

This vector represents the text document, with each number corresponding to the frequency of a specific word or feature.