22. A method of re-ranking a list of documents obtained from a search wherein a ranking of a document in the list is determined by a relevance of the document to a search text, and wherein each document in the list has a fingerprint, said fingerprint comprising a list of weights associated with particular topic categories in a classification system, each of the weights representing a degree to which the document related to the particular topic category that the weight is associated with, the weights obtained automatically from a computer program, the method having a scalable time complexity of O(N x ) where 0<=X<=1.0 for a universe of text on the world wide web and comprising: a computer processor creating a fingerprint for a first piece of text, the fingerprint comprising a list of weights associated with particular topic categories in the classification system, each of the weights in the fingerprint for said first piece of text representing a degree to which the first piece of text relates to the particular topic category that the weight in the fingerprint for the first piece of text is associated with, the weights in the fingerprint for said first piece of text obtained automatically from a computer program, a computer processor searching the list of documents by comparing the fingerprint for the first piece of text with the fingerprint for each document in the list of documents, re-ranking the list of documents based on a degree to which a fingerprint of a document in the list has a mathematically overlap with the fingerprint of the first piece of text, the method configured to re-rank the list of documents based on relevance to the search text whether the list of documents includes text written in one language or in more than one language.
22. A method of re-ranking a list of documents obtained from a search wherein a ranking of a document in the list is determined by a relevance of the document to a search text, and wherein each document in the list has a fingerprint, said fingerprint comprising a list of weights associated with particular topic categories in a classification system, each of the weights representing a degree to which the document related to the particular topic category that the weight is associated with, the weights obtained automatically from a computer program, the method having a scalable time complexity of O(N x ) where 0<=X<=1.0 for a universe of text on the world wide web and comprising: a computer processor creating a fingerprint for a first piece of text, the fingerprint comprising a list of weights associated with particular topic categories in the classification system, each of the weights in the fingerprint for said first piece of text representing a degree to which the first piece of text relates to the particular topic category that the weight in the fingerprint for the first piece of text is associated with, the weights in the fingerprint for said first piece of text obtained automatically from a computer program, a computer processor searching the list of documents by comparing the fingerprint for the first piece of text with the fingerprint for each document in the list of documents, re-ranking the list of documents based on a degree to which a fingerprint of a document in the list has a mathematically overlap with the fingerprint of the first piece of text, the method configured to re-rank the list of documents based on relevance to the search text whether the list of documents includes text written in one language or in more than one language. 23. The method of claim 22 , wherein either the weights are scaled or else the mathematical overlaps are scaled.