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    HEBBIAN LEARNING-BASED RECOMMENDATIONS FOR SOCIAL NETWORKS
    11.
    发明申请
    HEBBIAN LEARNING-BASED RECOMMENDATIONS FOR SOCIAL NETWORKS 审中-公开

    公开(公告)号：US20190312950A1

    公开(公告)日：2019-10-10

    申请号：US16437332

    申请日：2019-06-11

    Applicant: Verizon Patent and Licensing Inc.

    Inventor： Haripriya Srinivasaraghavan

    IPC: H04L29/08 ,  G06F11/34 ,  H04L12/26

    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.

    MULTI-DIMENSIONAL HIERARCHICAL CONTENT NAVIGATION
    12.
    发明申请
    MULTI-DIMENSIONAL HIERARCHICAL CONTENT NAVIGATION 审中-公开

    公开(公告)号：US20190289366A1

    公开(公告)日：2019-09-19

    申请号：US16434837

    申请日：2019-06-07

    Applicant: Verizon Patent and Licensing Inc.

    Inventor： Haripriya Srinivasaraghavan ,  Lakshmi N. Chakarapani

    IPC: H04N21/482

    Abstract: A device includes a display unit that displays a tile display comprising multiple rows and columns of tiles upon a display unit of a device, wherein each of the tiles represents an item of content or a group of items of content. The device associates multiple different linear axes with the tile display, wherein the multiple different linear axes intersect at a center tile of the tile display and wherein multiple different properties are associated with the center tile. The device receives user input associated with selecting one of the linear axes of the tile display; identifies a search parameter based on the selected one of the linear axes and based on at least one of the multiple different properties associated with the center tile; and causes the tile display to include search results resulting from a search of the content catalog with the identified search parameter.

    Hebbian learning-based recommendations for social networks
    13.
    发明授权
    Hebbian learning-based recommendations for social networks 有权

    公开(公告)号：US10362137B2

    公开(公告)日：2019-07-23

    申请号：US14979738

    申请日：2015-12-28

    Applicant: Verizon Patent and Licensing Inc.

    Inventor： Haripriya Srinivasaraghavan

    IPC: H04L12/26 ,  H04L29/08 ,  G06F11/34 ,  H04N21/25 ,  H04N21/258 ,  H04N21/45 ,  H04N21/466 ,  H04N21/4788 ,  H04N21/482 ,  H04N21/84

    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.

    REHEARSAL NETWORK FOR GENERALIZED LEARNING
    18.
    发明申请
    REHEARSAL NETWORK FOR GENERALIZED LEARNING 有权

    公开(公告)号：US20220222530A1

    公开(公告)日：2022-07-14

    申请号：US17705543

    申请日：2022-03-28

    Applicant: Verizon Patent and Licensing Inc.

    Inventor： Haripriya Srinivasaraghavan

    IPC: G06N3/08 ,  G06N3/04 ,  G06F17/18 ,  G06F16/78 ,  G06Q30/02

    Abstract: A method, a device, and a non-transitory storage medium are described in which a rehearsal network service is provided that enables generalized learning for all types of input patterns ranging from one-shot inputs to a large set of inputs. The rehearsal network service includes using biological memory indicator data relating to a user and the input data. The rehearsal network service includes calculating a normalized effective salience for each input data, and generating a new set of input data in which the inclusion of input data is proportional to its normalization effective salience. The rehearsal network service provides the new set of input data to a learning network, such as a neural network or a deep learning network that can learn the user's taste or preference.

    NATURAL LANGUAGE-BASED SEARCH AND DISCOVERY OF CONTENT SERVICE
    20.
    发明申请
    NATURAL LANGUAGE-BASED SEARCH AND DISCOVERY OF CONTENT SERVICE 有权

    公开(公告)号：US20210073302A1

    公开(公告)日：2021-03-11

    申请号：US16561554

    申请日：2019-09-05

    Applicant: Verizon Patent and Licensing Inc.

    Inventor： Haripriya Srinivasaraghavan ,  Praveen Kumar Bandaru

    IPC: G06F16/9532 ,  G06F16/9535 ,  G06F16/9538 ,  G06F17/27

    Abstract: A method, a device, and a non-transitory storage medium are described, which provide a natural language-based content search and discovery service. The natural language-based content search and discovery service may use query object types as a basis for interpreting a vocalized search query from a user. The natural language-based content search and discovery service may use a multi-interpretative procedure that includes use of a probabilistic grammar parser, parts of speech, and query object type identification that are configured for a media domain. The natural language-based content search and discovery service may merge different interpretations of the search query based on probability values associated with each interpretation.

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