16. The non-transitory CRM of claim 14 , wherein vectorizing tokenized sentences of the reference document and of the archived document is performed using a k-skip-n-gram vectorization, wherein skip-grams of a length n with a maximum number of skipped tokens k are generated; and wherein each skip-gram is separately vectorized.
14. A non-transitory computer readable medium (CRM) storing instructions for assessing similarity of documents, the instructions comprising functionality for: extracting a reference document text from a reference document; extracting an archived document text from an archived document; quantifying the reference document, comprising: tokenizing sentences of the reference document; and vectorizing the tokenized sentences to obtain a reference document text vector for each sentence of the reference document; quantifying the archived document, comprising: tokenizing sentences of the archived document; and vectorizing the tokenized sentences to obtain an archived document text vector for each sentence of the archived document; determining a document similarity value of the quantified reference document and the quantified archived document, comprising: calculating a plurality of vector similarity values for a plurality of combinations of a reference document text vector and an archived document text vector, the calculating including multiplying each of the vector similarity values of the plurality of vector similarity values with a corresponding weight that is determined, based at least in part on a number of skipped tokens; and calculating the document similarity value, comprising a sum of the plurality of vector similarity values.