Abstract class for string similarities that rely on set operations (like cosine similarity or jaccard index). k-shingling is the operation of transforming a string (or text document) into a set of n-grams, which can be used to measure the similarity between two strings or documents. Generally speaking, a k-gram is any sequence of k tokens. We use here the definition from Leskovec, Rajaraman & Ullman (2014), "Mining of Massive Datasets", Cambridge University Press: Multiple subsequent spaces are replaced by a single space, and a k-gram is a sequence of k characters. Default value of k is 3. A good rule of thumb is to imagine that there are only 20 characters and estimate the number of k-shingles as 20^k. For small documents like e-mails, k = 5 is a recommended value. For large documents, such as research articles, k = 9 is considered a safe choice.