31. The system according to claim 1 wherein said document rater comprises an electronic document analysis system comprising: an electronic analyzer operative to generate a predetermined output characterizing a set of electronic documents; and an electronic analyzer evaluation system operative to receive an additional output regarding said set of electronic documents whose additional output was generated by an external electronic document analysis system and to compare said predetermined output and said additional output in order to validate said electronic analyzer vis a vis said external electronic document analysis system.
1. A system for computerized derivation of leads from a huge body of data, the system comprising: an electronic repository including a multiplicity of accesses to a respective multiplicity of electronic documents and metadata including metadata parameters having metadata values characterizing each of said multiplicity of electronic documents; a document rater using a processor to run a first computer algorithm on said multiplicity of electronic documents which yields a score which rates each of said multiplicity of electronic documents; and a metadata-based document discriminator using the processor to run a second computer algorithm on at least some of said metadata which yields leads, each lead comprising at least one metadata value for at least one metadata parameter, whose value correlates with the score of said electronic documents, wherein said discriminator is operative to perform the following for each of a multiplicity of logical conditions defined over the individual documents' metadata: a. access a subset of said multiplicity of electronic documents wherein membership in said subset, of an individual document from among said multiplicity of electronic documents, is determined by whether or not a current logical condition defined over said individual documents' metadata, is true; b. compute at least one first value, including a proportion of documents having a relevance score whose value is “relevant”, over at least one subset; c. Provide a second value including a proportion of documents having a relevance score whose value is “relevant” from among all of said multiplicity of electronic documents; and d. compare said first value to the second value, define said logical condition defined over said individual documents' metadata as a lead when said first and second values differ by at least a predetermined extent and generate an output indication of the lead.