Method For Generating Rules and Parameters for Assessing Relevance of Information Derived From Internet Traffic
First Claim
1. A method comprising the steps of:
- receiving a sample volume of information requests originating at a network access device for processing in accordance with a request/response protocol;
recording an indication of whether each information request of the sample volume was invoked by action of a network access device user or by a prior information request;
examining the response to each received information request of the sample volume to identify its file type;
storing an indication of the file type of the response to each received information request of the sample volume;
applying an evaluation engine using at least one initial criterion to thereby establish an approximate boundary between those information requests invoked by an action of a network access device user and those information requests invoked by a prior information request;
classifying each information request of the sample volume as invoked by action of a network access device user or by a prior information request on the basis of whether or not the at least one criterion is satisfied;
measuring a distance between a number of information requests classified as being invoked by the user and an actual number of information requests invoked by the user;
measuring an overall ratio of information requests classified as being invoked by the user to an overall number of information requests before and after modifying the at least one initial criterion applied by the evaluation engine; and
repeating the classifying and modifying steps until there is no significant improvement of the measured distance to be obtained.
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Abstract
A method is disclosed for generating a set of optimal rules and parameters for use by an evaluation engine on a volume of information extracted from a stream of IP packets associated with a web browsing session conducted over a network in order to filter user-initiated traffic flowing across the network from non-user-initiated traffic. Deep packet inspection is performed to extract the volume of information from the stream that conforms to at least one discrimination criteria. An initial iteration of application of the evaluation engine to the volume is performed by selecting initial discrimination criteria and rules for generating the filtered results and a distance between the filtered results and known actual user-initiated traffic is measured. Subsequent iterations of application of the evaluation engine to the volume are performed by changing the discrimination criteria and/or rules until there is no significant improvement in the measured distance.
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Citations
20 Claims
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1. A method comprising the steps of:
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receiving a sample volume of information requests originating at a network access device for processing in accordance with a request/response protocol; recording an indication of whether each information request of the sample volume was invoked by action of a network access device user or by a prior information request; examining the response to each received information request of the sample volume to identify its file type; storing an indication of the file type of the response to each received information request of the sample volume; applying an evaluation engine using at least one initial criterion to thereby establish an approximate boundary between those information requests invoked by an action of a network access device user and those information requests invoked by a prior information request; classifying each information request of the sample volume as invoked by action of a network access device user or by a prior information request on the basis of whether or not the at least one criterion is satisfied; measuring a distance between a number of information requests classified as being invoked by the user and an actual number of information requests invoked by the user; measuring an overall ratio of information requests classified as being invoked by the user to an overall number of information requests before and after modifying the at least one initial criterion applied by the evaluation engine; and repeating the classifying and modifying steps until there is no significant improvement of the measured distance to be obtained. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. One or more computer-readable storage media containing instructions which, when executed by one or more processors disposed in an electronic device, perform a method for applying an evaluation engine, the method comprising the steps of:
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generating a volume of test data associated with a web browsing session conducted at least in part over a communications network between a network access device and a remote server by applying one or more discrimination criteria to a stream of IP packets associated with the web browsing session; ascertaining known true clicks and known false clicks associated with the volume of test data by observing the behavior of the network access device or a user of the network access device during the web browsing session; using an evaluation engine that includes one or more deterministic rules or one or more evaluative rules that are applied to the volume of test data to generate a set of filtered results comprising modeled true clicks; and comparing the modeled true clicks in the set of filtered results to the known true clicks to evaluate performance of the evaluation engine. - View Dependent Claims (12, 13, 14, 15, 16)
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17. A computer-implemented method for applying an evaluation engine for distinguishing between true clicks and false clicks in a web browsing session between a network access device and a remote server, the method comprising the steps of:
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configuring a network intelligence solution with access to a stream of IP packets utilized in the web browsing session so that the network intelligence solution may tap at least a portion of the IP packets; applying deep packet inspection to the tapped IP packets to extract selected information from the IP packets according to discrimination criteria, the discrimination criteria including at least one of technical data, page information, or timing-based information; applying an evaluation engine incorporating rules arranged for filtering the extracted information to substantially include true clicks and substantially exclude false clicks, the rules being deterministic or implementing aggregative evaluation of each of the discrimination criteria; and comparing a result of application of the evaluation engine to the extracted information against known true clicks that are observed to occur during the web browsing session. - View Dependent Claims (18, 19, 20)
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Specification