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公开(公告)号：US11907987B2
公开(公告)日：2024-02-20
申请号：US17550245
申请日：2021-12-14
发明人： Estelle Afshar , Matthew Hagen , Huiming Qu
CPC分类号： G06Q30/0623 , G06F18/22 , G06N3/045 , G06N3/08 , G06V10/761 , G06V10/806
摘要： A computer-implemented method for determining image similarity includes determining, by a first neural network, a first feature value associated with a first characteristic of a first product based on an image of the first product. The method also includes determining, by a second neural network, a second feature value associated with a second characteristic of the first product based on the image of the first product. The method further involves calculating a first vector space distance between the first feature value and a third feature value associated with the first characteristic of a second product, and calculating a second vector space distance between the second feature value and a fourth feature value associated with the second characteristic of the second product. Additionally, the method includes determining a similarity value based on the first vector space distance and the second vector space distance.
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公开(公告)号：US20220253643A1
公开(公告)日：2022-08-11
申请号：US17550245
申请日：2021-12-14
发明人： Estelle Afshar , Matthew Hagen , Huiming Qu
摘要： A computer-implemented method for determining image similarity includes determining, by a first neural network, a first feature value associated with a first characteristic of a first product based on an image of the first product. The method also includes determining, by a second neural network, a second feature value associated with a second characteristic of the first product based on the image of the first product. The method further involves calculating a first vector space distance between the first feature value and a third feature value associated with the first characteristic of a second product, and calculating a second vector space distance between the second feature value and a fourth feature value associated with the second characteristic of the second product. Additionally, the method includes determining a similarity value based on the first vector space distance and the second vector space distance.
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公开(公告)号：US20210326370A1
公开(公告)日：2021-10-21
申请号：US17234033
申请日：2021-04-19
发明人： Xiquan Cui , Rebecca West , Khalifeh Al Jadda , Huiming Qu
IPC分类号： G06F16/33 , G06Q30/06 , G06F16/383 , G06F16/9035 , G06F16/908 , G06F16/31
摘要： A computer-implemented method includes extracting, by one or more processors of one or more computing devices, a product family name from each of a plurality of unstructured product titles associated with a plurality of products. The method further includes determining, by the one or more processors, a degree of similarity between model numbers of the plurality of products. The method further includes determining, by the one or more processors, that at least two of the plurality of products are variants of one another by determining that the at least two of the plurality of products have a same extracted product family name and determining that the degree of similarity between the model numbers of the plurality of products is above a predetermined threshold.
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公开(公告)号：US20240112244A1
公开(公告)日：2024-04-04
申请号：US18530816
申请日：2023-12-06
发明人： Khalifeh Al Jadda , Huiming Qu , Nian Yan , San He Wu , Unaiza Ahsan
IPC分类号： G06Q30/0601 , G06F16/28 , G06F16/9535 , G06N3/08
CPC分类号： G06Q30/0631 , G06F16/285 , G06F16/9535 , G06N3/08
摘要： A method includes determining a first taxonomy of an anchor product. The first taxonomy includes a plurality of levels for classifying products organized from a highest taxonomy level to a lowest level. The method further includes determining a second taxonomy closest to the first taxonomy. The second taxonomy is associated with a group of products, the first taxonomy and the second taxonomy have at least a common highest taxonomy level, and the determination is made at least in part based on co-purchase data indicating that the anchor product and at least one product in the group of products are purchased together more often than products associated with other taxonomies are purchased with the anchor product. The method further includes determining a most similar product to the anchor product from the group of products of the second taxonomy and associating the anchor product and the most similar product in a collection.
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公开(公告)号：US20180047083A1
公开(公告)日：2018-02-15
申请号：US15233804
申请日：2016-08-10
发明人： Shubham Agarwal , Huiming Qu , Shawn Coombs , Estelle Afshar , Rini Devnath , Ramesh Gundeti , Prat Vemana , Kevin Hofmann
CPC分类号： G06Q30/0631 , G06Q30/012 , G06Q30/0641
摘要： This disclosure includes systems and methods for providing purchase recommendations to a user that may include items frequently purchased with a product selected by the user. The determination of which items are frequently purchased with which other items may account for both online and in-store transactions and may further account for both pairwise and multi-wise relationships. The recommendations may be provided on an electronic user interface, such as a website, in response to the user's selection of the product through the electronic user interface. The recommendations may be tailored to the user's selected product so that the recommended items are available in the same delivery channel as the user-selected product.
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公开(公告)号：US11200445B2
公开(公告)日：2021-12-14
申请号：US16749629
申请日：2020-01-22
发明人： Estelle Afshar , Matthew Hagen , Huiming Qu
摘要： A computer-implemented method for determining image similarity includes determining, by a first neural network, a first feature value associated with a first characteristic of a first product based on an image of the first product. The method also includes determining, by a second neural network, a second feature value associated with a second characteristic of the first product based on the image of the first product. The method further involves calculating a first vector space distance between the first feature value and a third feature value associated with the first characteristic of a second product, and calculating a second vector space distance between the second feature value and a fourth feature value associated with the second characteristic of the second product. Additionally, the method includes determining a similarity value based on the first vector space distance and the second vector space distance.
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公开(公告)号：US10991026B2
公开(公告)日：2021-04-27
申请号：US15233804
申请日：2016-08-10
发明人： Shubham Agarwal , Huiming Qu , Shawn Coombs , Estelle Afshar , Rini Devnath , Ramesh Gundeti , Prat Vemana , Kevin Hofmann
摘要： This disclosure includes systems and methods for providing purchase recommendations to a user that may include items frequently purchased with a product selected by the user. The determination of which items are frequently purchased with which other items may account for both online and in-store transactions and may further account for both pairwise and multi-wise relationships. The recommendations may be provided on an electronic user interface, such as a website, in response to the user's selection of the product through the electronic user interface. The recommendations may be tailored to the user's selected product so that the recommended items are available in the same delivery channel as the user-selected product.
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公开(公告)号：US11861675B2
公开(公告)日：2024-01-02
申请号：US16785104
申请日：2020-02-07
发明人： Khalifeh Al Jadda , Huiming Qu , Nian Yan , Unaiza Ahsan , San He Wu
IPC分类号： G06Q30/0601 , G06N3/08 , G06F16/9535 , G06F16/28
CPC分类号： G06Q30/0631 , G06F16/285 , G06F16/9535 , G06N3/08
摘要： A method includes determining a first taxonomy of an anchor product. The first taxonomy includes a plurality of levels for classifying products organized from a highest taxonomy level to a lowest taxonomy level. The method further includes determining a second taxonomy closest to the first taxonomy. The second taxonomy is associated with a group of products, the first taxonomy and the second taxonomy have at least a common highest taxonomy level, and the determination is made at least in part based on co-purchase data indicating that the anchor product and at least one product in the group of products are purchased together more often than products associated with other taxonomies are purchased with the anchor product. The method further includes determining a most similar product to the anchor product from the group of products of the second taxonomy and associating the anchor product and the most similar product with one another in a product collection.
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公开(公告)号：US11687841B2
公开(公告)日：2023-06-27
申请号：US16894344
申请日：2020-06-05
发明人： Matthew Hagen , Estelle Afshar , Huiming Qu , Ala Eddine Ayadi , Jiaqi Wang
IPC分类号： G06N20/20 , G06N20/00 , G06F18/214 , G06F18/23 , G06F18/21 , G06V10/762 , G06V10/764 , G06V10/774 , G06V10/82
CPC分类号： G06N20/20 , G06F18/217 , G06F18/2148 , G06F18/2155 , G06F18/23 , G06N20/00 , G06V10/763 , G06V10/764 , G06V10/7747 , G06V10/82
摘要： A method for machine learning-based classification may include training a machine learning model with a full training data set, the full training data set comprising a plurality of data points, to generate a first model state of the machine learning model, generating respective embeddings for the data points in the full training data set with the first model state of the machine learning model, applying a clustering algorithm to the respective embeddings to generate one or more clusters of the embeddings, identifying outlier embeddings from the one or more clusters of the embeddings, generating a reduced training data set comprising the full training data set less the data points associated with the outlier embeddings, training the machine learning model with the reduced training data set to a second model state, and applying the second model state to one or more data sets to classify the one or more data sets.
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公开(公告)号：US20210224582A1
公开(公告)日：2021-07-22
申请号：US16749629
申请日：2020-01-22
发明人： Estelle Afshar , Matthew Hagen , Huiming Qu
摘要： A computer-implemented method for determining image similarity includes determining, by a first neural network, a first feature value associated with a first characteristic of a first product based on an image of the first product. The method also includes determining, by a second neural network, a second feature value associated with a second characteristic of the first product based on the image of the first product. The method further involves calculating a first vector space distance between the first feature value and a third feature value associated with the first characteristic of a second product, and calculating a second vector space distance between the second feature value and a fourth feature value associated with the second characteristic of the second product. Additionally, the method includes determining a similarity value based on the first vector space distance and the second vector space distance.
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