Hierarchical behavioral profile
First Claim
1. A computer-implemented method for creating a hierarchical profile for an entity, the method comprising:
- collecting, by one or more computing devices, behavioral data associated with the entity;
identifying, by the one or more computing devices, a plurality of features of the collected data;
based, at least in part, on an analysis of at least a portion of the collected behavioral data, selecting, by the one or more computing devices, a first feature of the identified features, wherein the first feature is selected as the statistically most informative feature of the analyzed behavioral data based at least in part on statistical weights respectively associated with the identified features;
based, at least in part, on an analysis of at least a portion of the collected behavioral data, selecting, by the one or more computing devices, a plurality of values for the selected first feature;
creating, by the one or more computing devices, a first hierarchical preference level in the profile, the first level based, at least in part, on the selected first feature that is statistically most informative and the selected values for the selected first feature;
defining a coverage criterion for the profile;
based, at least in part, on an analysis of at least a portion of the collected behavioral data, selecting, by the one or more computing devices, a second feature of the identified features, the second feature distinct from the first feature;
based, at least in part, on an analysis of at least a portion of the collected behavioral data, selecting, by the one or more computing devices, a plurality of values for the selected second feature;
creating, by the one or more computing devices, a second hierarchical preference level in the profile, the second level based, at least in part, on the selected second feature and the selected values for the selected second feature; and
repeating the selecting and creating steps with distinct features until the coverage criterion is satisfied.
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Abstract
In a hierarchical profile, each node represents at least one feature of behavioral data collected about an entity profiled, with the topmost node selected as the “statistically most informative” feature of the data. A profile can cover numerous domains and be predictively very powerful in each domain. A number of observations can be “aggregated” together into a single datapoint. In use, the structure of the profile is compared against current information associated with the entity to produce a recommendation or prediction. If the profile represents at least some data aggregation, then new observations are folded into the profile based on statistical weights of the aggregations. Because of the way the profile is created and updated, its hierarchical structure maps the collected observations. Therefore, as new observations are incorporated, if the new observations change the profile'"'"'s structure significantly, then it can be hypothesized that something “interesting” has happened to the entity.
40 Citations
32 Claims
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1. A computer-implemented method for creating a hierarchical profile for an entity, the method comprising:
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collecting, by one or more computing devices, behavioral data associated with the entity; identifying, by the one or more computing devices, a plurality of features of the collected data; based, at least in part, on an analysis of at least a portion of the collected behavioral data, selecting, by the one or more computing devices, a first feature of the identified features, wherein the first feature is selected as the statistically most informative feature of the analyzed behavioral data based at least in part on statistical weights respectively associated with the identified features; based, at least in part, on an analysis of at least a portion of the collected behavioral data, selecting, by the one or more computing devices, a plurality of values for the selected first feature; creating, by the one or more computing devices, a first hierarchical preference level in the profile, the first level based, at least in part, on the selected first feature that is statistically most informative and the selected values for the selected first feature; defining a coverage criterion for the profile; based, at least in part, on an analysis of at least a portion of the collected behavioral data, selecting, by the one or more computing devices, a second feature of the identified features, the second feature distinct from the first feature; based, at least in part, on an analysis of at least a portion of the collected behavioral data, selecting, by the one or more computing devices, a plurality of values for the selected second feature; creating, by the one or more computing devices, a second hierarchical preference level in the profile, the second level based, at least in part, on the selected second feature and the selected values for the selected second feature; and repeating the selecting and creating steps with distinct features until the coverage criterion is satisfied. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16)
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17. A first computing device configured for creating a hierarchical profile for an entity, the first computing device comprising:
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a transceiver configured for collecting behavioral data associated with the entity; and a processor operatively connected to the transceiver and configured for; identifying a plurality of features of the collected data; based, at least in part, on an analysis of at least a portion of the collected behavioral data, selecting a first feature of the identified features, wherein the first feature is selected as the statistically most informative feature of the analyzed behavioral data based at least in part on statistical weights respectively associated with the identified features; based, at least in part, on an analysis of at least a portion of the collected behavioral data, selecting a plurality of values for the selected first feature; creating a first hierarchical preference level in the profile, the first level based, at least in part, on the selected first feature that is statistically most informative and the selected values for the selected first feature; defining a coverage criterion for the profile; based, at least in part, on an analysis of at least a portion of the collected behavioral data, selecting a second feature of the identified features, the second feature distinct from the first feature; based, at least in part, on an analysis of at least a portion of the collected behavioral data, selecting a plurality of values for the selected second feature; creating a second hierarchical preference level in the profile, the second level based, at least in part, on the selected second feature and the selected values for the selected second feature; and repeating the selecting and creating steps with distinct features until the coverage criterion is satisfied. - View Dependent Claims (18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32)
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Specification