HEBBIAN LEARNING-BASED RECOMMENDATIONS FOR SOCIAL NETWORKS
First Claim
1. A method comprising:
- obtaining, by a network device, customer activity data for a content-based social network;
modeling, by the network device, the customer activity data as nodes and edges within the content-based social network, the nodes representing users and the edges representing connections between the users;
assigning, by the network device, initial weights to the edges, that correspond to a connection strength, based on user-designated of relationships between the nodes;
adjusting, by the network device, the initial weights in response to temporally correlated activity between the nodes from the customer activity data, to provide adjusted weights;
identifying, by the network device, a content recommendation for a particular node based on an activity to access content by another node and one or more of the adjusted weights;
storing, by the network device, a customer profile including the content recommendations associated with a node; and
providing, by the network device, the content recommendation to a user device associated with the customer profile.
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Abstract
A network device applies Hebbian-based learning to provide content recommendations in content-based social networks. The method includes obtaining customer activity data for a content-based social network; modeling the customer activity data as nodes and edges within the content-based social network, the nodes representing users and the edges representing connections between the users; assigning initial weights to the edges, that correspond to a connection strength, based on user-designated of relationships between the nodes; adjusting the initial weights in response to temporally correlated activity between the nodes from the customer activity data, to provide adjusted weights; identifying a content recommendation for a particular node based on an activity to access content by another node and one or more of the adjusted weights; storing a customer profile including the content recommendations associated with a node; and providing the content recommendation to a user device associated with the customer profile.
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Citations
20 Claims
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1. A method comprising:
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obtaining, by a network device, customer activity data for a content-based social network; modeling, by the network device, the customer activity data as nodes and edges within the content-based social network, the nodes representing users and the edges representing connections between the users; assigning, by the network device, initial weights to the edges, that correspond to a connection strength, based on user-designated of relationships between the nodes; adjusting, by the network device, the initial weights in response to temporally correlated activity between the nodes from the customer activity data, to provide adjusted weights; identifying, by the network device, a content recommendation for a particular node based on an activity to access content by another node and one or more of the adjusted weights; storing, by the network device, a customer profile including the content recommendations associated with a node; and providing, by the network device, the content recommendation to a user device associated with the customer profile. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A device comprising:
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one or more memories to store instructions; and one or more processing systems to execute the instructions that configure the one or more processing systems to; obtain customer activity data for a content-based social network; model the customer activity data as nodes and edges within the content-based social network, the nodes representing users and the edges representing connections between the users; assign initial weights to the edges, that correspond to a connection strength, based on user-designated of relationships between the nodes; adjust the initial weights in response to temporally correlated activity between the nodes from the customer activity data, to provide adjusted weights; identify a content recommendation for a particular node based on an activity to access content by another node and one or more of the adjusted weights; store, a customer profile including the content recommendations associated with a node; and provide the content recommendation to a user device associated with the customer profile. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17)
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18. A non-tangible computer-readable medium storing instructions for:
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obtaining customer activity data for a content-based social network; modeling the customer activity data as nodes and edges within the content-based social network, the nodes representing users and the edges representing connections between the users; assigning initial weights to the edges, that correspond to a connection strength, based on user-designated of relationships between the nodes; adjusting the initial weights in response to temporally correlated activity between the nodes from the customer activity data, to provide adjusted weights; identifying a content recommendation for a particular node based on an activity to access content by another node and one or more of the adjusted weights; storing a customer profile including the content recommendations associated with a node; and providing the content recommendation to a user device associated with the customer profile. - View Dependent Claims (19, 20)
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Specification