Method and system for determining the geographic location of a network block
First Claim
1. A method of assigning a geographic location to a network block comprising:
- obtaining geo-location data from a plurality of network data sources;
generating, for each data source, intermediate assignments associated with a network block, each intermediate assignment corresponding to geo-location assignment of the network block based on at least one of the network data sources;
generating a plurality of feature vectors, each feature vector including a plurality of attributes associated with a different network data source of the plurality of network data sources, a value for a particular attribute of the plurality of attributes representing a degree to which that attribute is present or absent in a corresponding network data source of the plurality of network data sources;
classifying and/or regressing each intermediate assignment using the plurality of feature vectors to generate classifications and/or regressions based on training data, the classifications being a mapping from a discrete or continuous feature space to a discrete set of labels, the training data including a set of feature vectors and corresponding desired outputs for each of the feature vectors of the set of feature vectors; and
determining a geographic location of the network block based upon at least one of the intermediate assignment classifications and/or regressions.
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Abstract
Described herein are a method and a system to assign geographic locations to network blocks. A particular embodiment of the system includes a set of intermediate assignment generators, each intermediate assignment generator being associated with at least one of a plurality of network data sources, each intermediate assignment generator being configured to generate an intermediate assignment for at least one of the plurality of network data sources, a set of classifiers each coupled to at least one of the intermediate assignment generators, each classifier being associated with at least one of the plurality of network data sources, each classifier being configured to generate at least one classification based on at least one of the intermediate assignments and corresponding training data, and an intermediate assignment selector to select a best intermediate assignment based on the classifications generated by the set of classifiers, the best intermediate assignment corresponding to a geographic location of a network block.
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Citations
25 Claims
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1. A method of assigning a geographic location to a network block comprising:
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obtaining geo-location data from a plurality of network data sources; generating, for each data source, intermediate assignments associated with a network block, each intermediate assignment corresponding to geo-location assignment of the network block based on at least one of the network data sources; generating a plurality of feature vectors, each feature vector including a plurality of attributes associated with a different network data source of the plurality of network data sources, a value for a particular attribute of the plurality of attributes representing a degree to which that attribute is present or absent in a corresponding network data source of the plurality of network data sources; classifying and/or regressing each intermediate assignment using the plurality of feature vectors to generate classifications and/or regressions based on training data, the classifications being a mapping from a discrete or continuous feature space to a discrete set of labels, the training data including a set of feature vectors and corresponding desired outputs for each of the feature vectors of the set of feature vectors; and determining a geographic location of the network block based upon at least one of the intermediate assignment classifications and/or regressions. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A network block geo-locator system comprising:
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a set of intermediate assignment generators, each intermediate assignment generator being associated with at least one of a plurality of network data sources, each intermediate assignment generator being configured to generate an intermediate assignment for at least one of the plurality of network data sources, the intermediate assignment corresponding to geo-location assignment of a network block based on the at least one network data source; a feature vector generator to generate a plurality of feature vectors, each feature vector including a plurality of attributes associated with a different network data source of the plurality of network data sources, a value for a particular attribute of the plurality of attributes representing a degree to which that attribute is present or absent in a corresponding network data source of the plurality of network data sources; a set of classifiers each coupled to the feature vector generator and at least one of the intermediate assignment generators, each classifier being associated with at least one of the plurality of network data sources, each classifier being configured to generate at least one classification and/or regression based on the plurality of feature vectors and at least one of the intermediate assignments and corresponding training data, the classification being a mapping from a discrete or continuous feature space to a discrete set of labels, the training data including a set of feature vectors and corresponding desired outputs for each of the feature vectors of the set of feature vectors; and an intermediate assignment generator to determine a geographic location of the network block based on the at least one classification and/or regression generated by the set of classifiers. - View Dependent Claims (12, 13, 14, 15, 16, 17)
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18. An article of manufacture comprising a non-transitory machine-readable storage medium having machine executable instructions embedded thereon, which when executed by a machine, cause the machine to:
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obtain geo-location data from a plurality of network data sources; generate, for each data source, intermediate assignments associated with a network block, each intermediate assignment corresponding to geo-location assignment of the network block based on at least one of the network data sources; generating a plurality of feature vectors, each feature vector including a plurality of attributes associated with a different network data source of the plurality of network data sources, a value for a particular attribute of the plurality of attributes representing a degree to which that attribute is present or absent in a corresponding network data source of the plurality of network data sources; classify and/or regress each intermediate assignment using the plurality of feature vectors to generate classifications and/or regressions based on training data, the classifications being a mapping from a discrete or continuous feature space to a discrete set of labels, the training data including a set of feature vectors and corresponding desired outputs for each of the feature vectors of the set of feature vectors; and determine a geographic location of the network block based upon at least one of the intermediate assignment classifications and/or regressions. - View Dependent Claims (19, 20, 21, 22, 23, 24, 25)
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Specification