Abstract: Systems and methods are disclosed for ranking electronic content using a trained topic model to correlate a collection of source content to externally specified target content. Unstructured content is converted to elemental sub-content or interrelated sub-content. A probability vector for the converted externally specified content is generated by use of trained topic model. The externally specified topic probability vector is correlated against a collection of source content, previously converted to vectors that were generated using the same topic model, and a plurality of correlation methods. Rank ordered correlation results are merged to provide the user with a ranked set of source content. Source content from the ranked results can be fed back into the system to adjust the target vector.