Systems and methods for using one or more networks to assess a metric about an entity
First Claim
1. A computer-implemented method for predicting a metric value for an entity associated with a query node in a graph that represents a network, the method comprising:
- for each pre-classified node in a set of pre-classified nodes, which comprises a set of whitelist nodes, from the network, determining a score that gauges a strength of connection between the pre-classified node to the query node, the strength of connection being obtained by performing the steps comprising;
responsive to a first condition of the set of pre-classified nodes having a number of nodes above a first threshold being true, performing the steps comprising;
performing a number of random walks in the graph from the query node in the graph and terminating at another node in the graph;
for at least each node in the graph at which a random walk terminates, keeping a counter of how many times a walk terminated at that node in the graph;
determining a ranking value between the query node and another node in the graph based at least in part by dividing the number of times walks terminated on the another node by the number of random walks; and
using one or more ranking values to obtain a score that measures a strength of connection between the query node and the another node in the graph; and
generating a final value for the metric for the query node, the final value comprising a combination of at least one of the scores that gauges strength of connection between the pre-classified nodes of the set of pre-classified nodes to the query node.
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Abstract
Described herein are systems and methods for predicting a metric value for an entity associated with a query node in a graph that represents a network. In embodiments, using a user'"'"'s profile as the query node, a metric about that user may be estimated based, at least in part, as a function of how well connected the query node is to a whitelist of “good” users/nodes in the network, a blacklist of “bad” users/nodes in the network, or both. In embodiments, one or more nodes or edges may be weighted when determining a final score for the query node. In embodiments, the final score regarding the metric may be used to take one or more actions relative to the query node, including accepting it into a network, allowing or rejecting a transaction, assigning a classification to the node, using the final score to compute another estimate for a node, etc.
20 Citations
19 Claims
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1. A computer-implemented method for predicting a metric value for an entity associated with a query node in a graph that represents a network, the method comprising:
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for each pre-classified node in a set of pre-classified nodes, which comprises a set of whitelist nodes, from the network, determining a score that gauges a strength of connection between the pre-classified node to the query node, the strength of connection being obtained by performing the steps comprising; responsive to a first condition of the set of pre-classified nodes having a number of nodes above a first threshold being true, performing the steps comprising; performing a number of random walks in the graph from the query node in the graph and terminating at another node in the graph; for at least each node in the graph at which a random walk terminates, keeping a counter of how many times a walk terminated at that node in the graph; determining a ranking value between the query node and another node in the graph based at least in part by dividing the number of times walks terminated on the another node by the number of random walks; and using one or more ranking values to obtain a score that measures a strength of connection between the query node and the another node in the graph; and generating a final value for the metric for the query node, the final value comprising a combination of at least one of the scores that gauges strength of connection between the pre-classified nodes of the set of pre-classified nodes to the query node. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A system for predicting a metric value for an entity associated with a query node in a graph that represents a network, the system comprising:
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one or more processors; and a non-transitory computer-readable medium or non-transitory computer-readable media comprising one or more sequences of instructions which, when executed by the one or more processors, causes steps to be performed comprising; for each pre-classified node in a set of pre-classified nodes, which comprises a set of whitelist nodes, from the network, determining a score that gauges a strength of connection between the pre-classified node to the query node, the strength of connection being obtained by performing the steps comprising; responsive to a first condition of the set of pre-classified nodes having a number of nodes above a first threshold being true, performing the steps comprising; performing a number of random walks in the graph from the query node in the graph and terminating at another node in the graph; for at least each node in the graph at which a random walk terminates, keeping a counter of how many times a walk terminated at that node in the graph; determining a ranking value between the query node and another node in the graph based at least in part by dividing the number of times walks terminated on the another node by the number of random walks; and using one or more ranking values to obtain a score that measures a strength of connection between the query node and the another node in the graph; and generating a final value for the metric for the query node, the final value comprising a combination of at least one of the scores that gauges strength of connection between the pre-classified nodes of the set of pre-classified nodes to the query node. - View Dependent Claims (9, 10, 11, 12, 13)
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14. A computer-implemented method for predicting a metric about an entity associated with a query node in a graph that represents a network, the method comprising:
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for each whitelist node in a set of whitelist nodes from the network, determining a score that measures a strength of connection of the query node with respect to the whitelist node by performing the steps comprising; performing a number of random walks in the graph from a start node in the graph and terminating at another node in the graph; keeping a counter of how many times a walk terminated at a node in the graph; determining an estimate of a strength of connection between the start node and another node in the graph comprising dividing the number of times walks terminated on the another node by the number of random walks; and using the estimate of a strength of connection to determine the score that measures a strength of connection; generating a whitelist blended value for the metric comprising a combination of the scores for the whitelist nodes in the set of whitelist nodes; for each blacklist node in a set of blacklist nodes from the network, determining a score that measures a strength of connection of the blacklist node with respect to the query node; generating a blacklist blended value for the metric comprising a combination of the scores for the blacklist nodes in the set of blacklist nodes; and generating a final score blended from the whitelist blended value and the blacklist blended value to obtain an overall score for the query node. - View Dependent Claims (15, 16, 17, 18)
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19. A non-transitory computer-readable medium or non-transitory computer-readable media comprising one or more sequences of instructions which, when executed by one or more processors, causes steps for predicting a metric about an entity associated with a query node in a graph that represents a network to be performed, the steps comprising:
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for each whitelist node in a set of whitelist nodes from the network, determining a score that measures a strength of connection of the query node with respect to the whitelist node by performing the steps comprising; performing a number of random walks in the graph from a start node in the graph and terminating at another node in the graph; keeping a counter of how many times a walk terminated at a node in the graph; determining an estimate of a strength of connection between the start node and another node in the graph comprising dividing the number of times walks terminated on the another node by the number of random walks; and using the estimate of a strength of connection to determine the score that measures a strength of connection; generating a whitelist blended value for the metric comprising a combination of the scores for the whitelist nodes in the set of whitelist nodes; for each blacklist node in a set of blacklist nodes from the network, determining a score that measures a strength of connection of the blacklist node with respect to the query node; generating a blacklist blended value for the metric comprising a combination of the scores for the blacklist nodes in the set of blacklist nodes; and generating a final score blended from the whitelist blended value and the blacklist blended value to obtain an overall score for the query node.
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Specification