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Abstract

A method for automated mapping of key terms to documents. Preferably a feature vector is generated for the key terms. Preferably such feature vectors are automatically generated by analyzing a corpus, but may optionally be generated manually, or using a combination of automated and manual processes. Next, preferably such feature vectors are weighted. Such weighting may optionally be performed manually, but more preferably is performed automatically. Next, a feature vector is optionally and preferably generated for the document, which preferably includes words and phrases that were extracted from the document but may optionally include words and phrases that do not appear in the document, such as synonyms and related. Each element in the document feature vector is preferably weighted. The feature vectors of the key terms and the feature vectors of the documents are compared, in order to produce relevancy scores, which are used to produce mapping between documents and key terms. This mapping may optionally be used for a wide variety of applications, such as for targeted advertising for example.

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