17. A computer-implemented method for querying a collection of documents according to document layout, comprising: providing in computer memory: a set of representative blocks, each representative block being representative of a respective cluster of layout blocks extracted from documents in the collection, a set of document indexes, each document index being representative of layout blocks of a respective document in the collection, each of the document indexes being assigned to a respective one of a set of document index clusters, and a representative document index for each document index cluster, each representative document index being derived from the document indexes assigned to the document index cluster; extracting layout blocks from an input document layout query; projecting the extracted layout blocks from the document layout query onto the set of representative blocks to generate a query document index; with a computer processor, computing a measure of similarity between the query document index and each of the representative document indexes in the set of representative document indexes; identifying a top document index cluster which includes the representative document index determined to have the greatest similarity to the query document index; computing a measure of similarity between each document index in the top document index cluster and the query index to identify a set of most similar documents; and outputting information on the documents in the set of most similar documents.
18. The method of claim 17 , wherein the query index comprises a vector and further including at least one of a) and b): a) each of the representative document indexes comprises a vector and wherein the computation of the similarity measure between the query index and each of the representative document indexes comprises assigning a first rank based on a cosine of the angle between the query vector and the representative document index vector; and b) each of the document indexes comprises a vector and wherein the computation of the similarity measure between the query index and each of the document indexes comprises assigning a second rank based on a cosine of the angle between the query vector and the document index vector.