 For example, in some such models, if is the function that maps a word to its -d vector representation, then

where ≈ is made precise by stipulating that its right-hand side must be the nearest neighbor of the value of the left-hand side.A positional language model assesses the probability of given words occurring close to one another in a text, not necessarily immediately adjacent.Similarly, bag-of-concepts models leverage the semantics associated with multi-word expressions such as "buy_christmas_present", even when they are used in information-rich sentences like "today I bought a lot of very nice Christmas presents".