SYSTEMS AND METHODS FOR GENERATING LEADS IN A NETWORK BY PREDICTING PROPERTIES OF EXTERNAL NODES
First Claim
1. A computerized method for predicting one or more desired properties of external nodes based on a selected group of nodes about which it is known whether the nodes have the desired properties, the method comprising:
- storing in one or more data structures a first data set regarding external nodes and a second data set regarding nodes in a selected group, each data set having one or more data items representing one or more events relating to or attributes of each node in the data set, the second data set including one or more types of data items not included in the first data set;
virtualizing the second data set regarding nodes into a modeled second data set after the first data set regarding external nodes at least by eliminating from the second data set the one or more data item types not included in the first data set;
modeling the virtualized second data set to identify from the modeled second data one or more modeled events or attributes of nodes in the selected group that are statistically likely to identify the nodes that have the desired properties; and
predicting which of the external nodes are statistically likely to have the one or more desired properties based on the identified plurality of modeled events or attributes and the events or attributes in the first data set.
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Abstract
The present invention is directed towards systems and methods for predicting one or more desired properties of external nodes or properties of their relations with internal nodes, based on a selected group of nodes about which it is known whether the nodes have the desired properties, or it is known whether they have a desired relation property with an internal node. The method comprises storing in one or more data structures a first data set regarding external nodes and a second data set regarding nodes with known properties in a selected group, each data set having one or more data items representing one or more events relating to or attributes of each node in the data set, the second data set including one or more types of data items not included in the first data set. The method then models the second data set to identify from the second data one or more modeled events or attributes of internal nodes in the selected group that are statistically likely to identify the nodes or their relations, that have the desired properties and predicts which of the external nodes are statistically likely to have the one or more desired properties, or desired relation property with internal node, based on the identified plurality of modeled events or attributes and the events or attributes in the first data set.
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Citations
55 Claims
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1. A computerized method for predicting one or more desired properties of external nodes based on a selected group of nodes about which it is known whether the nodes have the desired properties, the method comprising:
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storing in one or more data structures a first data set regarding external nodes and a second data set regarding nodes in a selected group, each data set having one or more data items representing one or more events relating to or attributes of each node in the data set, the second data set including one or more types of data items not included in the first data set; virtualizing the second data set regarding nodes into a modeled second data set after the first data set regarding external nodes at least by eliminating from the second data set the one or more data item types not included in the first data set; modeling the virtualized second data set to identify from the modeled second data one or more modeled events or attributes of nodes in the selected group that are statistically likely to identify the nodes that have the desired properties; and predicting which of the external nodes are statistically likely to have the one or more desired properties based on the identified plurality of modeled events or attributes and the events or attributes in the first data set. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32)
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33. A system for predicting one or more desired properties of external nodes based on a selected group of internal nodes about which it is known whether the internal nodes have the desired properties, the system comprising:
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a link pre-processor operative to analyze a first data set regarding external nodes and a second data set regarding internal nodes in a selected group; one or more data structures storing the first data set regarding external nodes and the second data set regarding internal nodes in a selected group, each data set having one or more data items representing one or more events relating to or attributes of each node in the data set, the second data set including one or more types of data items not included in the first data set; an intra-link virtualizer component operative to virtualize the second data set regarding internal nodes into a modeled second data set after the first data set regarding external nodes at least by eliminating from the second data set the one or more data item types not included in the first data set; a learning machine operative to model the virtualized second data set to identify from the modeled second data set a plurality of modeled events or attributes of internal nodes in the selected group that are statistically likely to identify the internal nodes that have the desired properties; a prediction module operative to predict the identified plurality of modeled events or attributes with the events or attributes in the first data set to predict which of the external nodes are statistically likely to have the one or more desired properties; and a provider lead data storage unit operative to store the external nodes statistically likely to have the one or more desired properties. - View Dependent Claims (34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55)
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Specification