1. A computerized method implemented using a processor and memory, the method comprising: extracting information from a first input document; retrieving one or more second documents based on the extracted information; identifying one or more of the second documents as more probably related to the first input document than one or more of the other second documents using a learning machine; and wherein the step of identifying the one or more of the second documents includes defining a multi-dimensional feature vector for each second document, with the vector having a set of features including a similarity feature indicating similarity of at least a portion of a second document to a portion of the first input document and processing the multi-dimensional feature vector using support-vector processing wherein each of the feature vectors is based on a title similarity score for one or more portions of a second document and a said first input document.