In order to speed and facilitate the navigation of the large and ultra large compound libraries, the extended or n-ary similarity indices were recently proposed. These novel indices have found a broad range of applications such as quantifying the chemical diversity of (large) molecular libraries, the graphical representation of chemical space through Chemical Library Networks, clustering, diversity selection, and identifying the most representative compound of a compound data set (the medoid).