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Proxy server using a statistical model

  • US 7,603,616 B2
  • Filed: 11/05/2004
  • Issued: 10/13/2009
  • Est. Priority Date: 01/28/2000
  • Status: Expired due to Fees
First Claim
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1. A computer-readable medium storing computer-executable instructions for retrieving one document in a plurality of documents from either a remote server or a local cache, the one document having been previously retrieved from the remote server and a copy thereof stored in the cache, that, when executed, comprise:

  • Maintaining historical information representing prior changes to the one document;

    the historical information representing prior changes to the one document comprises for one document, a change count representing the number of times the one document has been modified, an access count representing the number of times the one document has been retrieved from the remote server, a first access time representing the time the one document was first retrieved from the remote server, and a last access time representing the time the one document was last retrieved from the remote server;

    Initiating a document retrieval request procedure for retrieving particular documents in the plurality of documents;

    Determining whether to access the one document from the remote server or the local cache, wherein the determination is based on a probabilistic analysis of the historical information representing prior changes to the one document, wherein the probabilistic analysis comprises;

    Computing a probability that the one document has changed since the one document was last retrieved from the remote server, the probability that the one document has changed since the document was last retrieved from the remote server being computed without examining the one document andBeginning with a probability that a pre-defined proportion of documents in the plurality of documents has changed, training the probability that the pre-defined proportion of documents has changed using the historical information representing prior changes to the one document to achieve the probability that the one document has changed;

    Wherein the step of training the probability comprises;

    creating a timeline using the historical information, the timeline having representations thereon of no change intervals, change intervals, and no change chunk intervals;

    Training the document probability distribution for each no change interval;

    Training the document probability distribution for each change interval; and

    Training the document probability distribution for each no change chunk interval.

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