| 摘要 |
A system and method implemented by a computer for performing query based electronic document retrieval implementing a Markov process model adapted for determining a relationship or relevance between documents. The system ranks documents for retrieval based on their relevance measure. The model calculates the measure of relevance that a document from a given database is relevant to a given query. The method learns the Markov models mixture coefficients from the document database so as to maximize the relevance measure of the documents being retrieved. The method requires only that a similarity measure, D(d,d'), between two documents be specified. Any existing method may be used for generating a model that is at least as good as the chosen similarity measure.
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