The geometry of the resulting vectors was shown in <cite>[23]</cite> to capture word semantic similarity through the cosine similarity of the corresponding vectors as well as more complex semantic relationships through vector differences, such as vec("Madrid") -vec("Spain") + vec("France") ≈ vec("Paris").