Invention Grant
- Patent Title: Item recommendations using convolutions on weighted graphs
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Application No.: US17850701Application Date: 2022-06-27
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Publication No.: US11995702B2Publication Date: 2024-05-28
- Inventor: Amit Pande , Kai Ni
- Applicant: Target Brands, Inc.
- Applicant Address: US MN Minneapolis
- Assignee: Target Brands, Inc.
- Current Assignee: Target Brands, Inc.
- Current Assignee Address: US MN Minneapolis
- Agency: Merchant & Gould P.C.
- Main IPC: G06Q30/06
- IPC: G06Q30/06 ; G06F16/2457 ; G06F16/9535 ; G06Q10/087 ; G06Q30/0201 ; G06Q30/0601 ; G06N3/08

Abstract:
Methods and systems for generating item recommendations are disclosed. One method includes sampling from a weighted node-based graph to generate a sampled graph, wherein sampling includes selecting a plurality of nodes and, for each selected node, one or more node pairs. The selection of the node pairs is based at least in part based on a weight assigned to the node pair in the weighted node-based graph. The method further includes aggregating information from the one or more neighboring nodes into each corresponding node of the plurality of nodes in the sampled graph to generate a vector representation of the sampled graph. The method also includes applying a loss function to the vector representation of the sampled graph to generate a modified vector representation. The modified vector representation is used to generate, in response to identification of an item from an item collection, a selection of one or more recommended items from within the item collection.
Public/Granted literature
- US20220335501A1 ITEM RECOMMENDATIONS USING CONVOLUTIONS ON WEIGHTED GRAPHS Public/Granted day:2022-10-20
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