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    Systems and methods for generating efficient iterative recommendation structures
    3.
    发明授权
    Systems and methods for generating efficient iterative recommendation structures 有权

    公开(公告)号：US11361349B1

    公开(公告)日：2022-06-14

    申请号：US15991544

    申请日：2018-05-29

    Applicant: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY

    Inventor： Taylor Griffin Smith ,  Jason Matthew White ,  Joseph David Albright ,  Tim G. Sanidas

    IPC: G06Q30/02 ,  G06Q50/00

    Abstract: Systems and methods are described for generating efficient iterative electronic recommendation structures. In various aspects, one or more processors aggregate a plurality of ratings vectors, where each ratings vector is associated with a vector type and contains one or more content ranking metrics associated with one or more users. The one or more processors generate similarity pairing values from the plurality of ratings vectors, where each similarity pairing value is based on a similarity mapping between a first ratings vector and a second ratings vector. The one or more processors further generate an electronic recommendation structure based on the similarity pairing values, where the electronic recommendation structure includes a bi-directional look-up interface that is configured to return a bi-directional recommendation value after receiving a lookup request for either the vector type of the first ratings vector or the vector type of the second ratings vector.

    Systems and Methods for Generating Efficient Iterative Recommendation Structures
    5.
    发明申请
    Systems and Methods for Generating Efficient Iterative Recommendation Structures 有权

    公开(公告)号：US20220292552A1

    公开(公告)日：2022-09-15

    申请号：US17828846

    申请日：2022-05-31

    Applicant: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY

    Inventor： Taylor Griffin Smith ,  Jason Matthew White ,  Joseph David Albright ,  Tim G. Sanidas

    IPC: G06Q30/02 ,  G06Q50/00

    Abstract: Systems and methods are described for generating efficient iterative electronic recommendation structures. In various aspects, one or more processors aggregate a plurality of ratings vectors, where each ratings vector is associated with a vector type and contains one or more content ranking metrics associated with one or more users. The one or more processors generate similarity pairing values from the plurality of ratings vectors, where each similarity pairing value is based on a similarity mapping between a first ratings vector and a second ratings vector. The one or more processors further generate an electronic recommendation structure based on the similarity pairing values, where the electronic recommendation structure includes a bi-directional look-up interface that is configured to return a bi-directional recommendation value after receiving a lookup request for either the vector type of the first ratings vector or the vector type of the second ratings vector.

    SYSTEMS AND METHODS FOR PROVIDING USER OFFERS BASED ON EFFICIENT ITERATIVE RECOMMENDATION STRUCTURES
    6.
    发明申请
    SYSTEMS AND METHODS FOR PROVIDING USER OFFERS BASED ON EFFICIENT ITERATIVE RECOMMENDATION STRUCTURES 有权

    公开(公告)号：US20210383419A1

    公开(公告)日：2021-12-09

    申请号：US17411209

    申请日：2021-08-25

    Applicant: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY

    Inventor： Taylor Griffin Smith ,  Jason Matthew White ,  Joseph David Albright ,  Tim G. Sanidas

    IPC: G06Q30/02 ,  G06F16/9535

    Abstract: Systems and methods are described for providing user offers based on efficient iterative recommendation structures. In various aspects, a server invokes a bi-directional look-up interface via a lookup request, where the bi-directional look-up interface is exposed via an electronic recommendation structure. The lookup request causes the bi-directional look-up interface to return a bi-directional recommendation value. The bi-directional recommendation value indicates a likelihood of a first user selecting a first offer or a second offer. The bi-directional recommendation value is transmitted via a computer network to a client device associated with the first user upon a determination that the likelihood meets or exceeds a recommendation threshold. The client device is operative to display at least one of the first offer or the second offer.

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