System and methods for computerized information governance of electronic documents

An information governance method comprising:

• generating a plurality of classifiers for classifying electronic documents into a corresponding plurality of documentation retention categories;
• running training iterations thereby to improve at least one of the plurality of classifiers;
• classifying a repository of electronic documents using said plurality of classifiers and running a Logarithmic stratified sampling-based Quality Assurance process to compute precision in cases of low or unknown richness including ordering documents by their ranks then partitioning the ranks into slices:
• [0,p] [p, 2p], [2p, 4p], . . . , and randomly selecting documents to represent each slice, thereby to generate Quality Assurance results;
• if the Quality Assurance results are not deemed good enough, improve the classifier and return to one of said running steps:
• if the Quality Assurance results are good enough, use last classifier to implement a plurality of document retention settings corresponding to said plurality of documentation retention categories.

A computer program product, comprising a non-transitory tangible computer readable medium having computer readable program code embodied therein, said computer readable program code adapted to be executed to implement an information governance method comprising:

• generating a plurality of classifiers for classifying electronic documents into a corresponding plurality of documentation retention categories;
• running training iterations thereby to improve at least one of the plurality of classifiers;
• classifying a repository of electronic documents using said plurality of classifiers and running a Logarithmic stratified sampling-based Quality Assurance process to compute precision in cases of low or unknown richness including ordering documents by their ranks then partitioning the ranks into slices:
• [0,p] [p, 2p], [2p, 4p], . . . , and randomly selecting documents to represent each slice, thereby to generate Quality Assurance results;
• if the Quality Assurance results are not deemed good enough, improve the classifier and return to one of said running steps;
• if the Quality Assurance results are good enough, use last classifier to implement a plurality of document retention settings corresponding to said plurality of documentation retention categories.