6. The method of claim 3 , wherein said converting step is completed by a parser function and includes: dividing each line of the database into tokens, each token being a word that is separated by a space, wherein each line within said database is split into words separated by a blank space; generating a dictionary of tokens comprising a single occurrence of each token, wherein duplication of tokens within the dictionary of tokens is substantially avoided; and converting each line of said database into a token vector with one entry for each token within the line.
6. The method of claim 3 , wherein said converting step is completed by a parser function and includes: dividing each line of the database into tokens, each token being a word that is separated by a space, wherein each line within said database is split into words separated by a blank space; generating a dictionary of tokens comprising a single occurrence of each token, wherein duplication of tokens within the dictionary of tokens is substantially avoided; and converting each line of said database into a token vector with one entry for each token within the line. 8. The method of claim 6 , further comprising: combining similar event examples into clusters; outputting said clusters to a user; and enabling user manipulation of parameters of said clustering algorithm to produce different clusters from those clusters originally outputted.