In this paper, we review the concept of contextual probability, the resulting notion of neighbourhood counting and the various specialisations of this notion which result in new functions for measuring similarity, such as all common subsequences. We also provide new results on the generalisation of the all common subsequences similarity. Contextual probability was originally proposed as an alternative way of reasoning. It was later found to be an alternative way of estimating probability, and it led to the introduction of the neighbourhood counting notion. This notion was then found to be a generic similarity metric that can be applied to different types of data.