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公开(公告)号：US20220138826A1
公开(公告)日：2022-05-05
申请号：US17088134
申请日：2020-11-03
Applicant: eBay Inc.
Inventor： Dingxian Wang
IPC: G06Q30/06 , G06F16/9538 , G06N5/02
Abstract: Various embodiments improve search technologies and computer information retrieval by executing a query via ranking a set of search result candidates higher than another set search result candidates based at least in part on the query and determining that a first set of search result candidates are indicative of a sub-accessory to an accessory or an accessory itself.
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公开(公告)号：US11663225B2
公开(公告)日：2023-05-30
申请号：US17402034
申请日：2021-08-13
Applicant: eBay Inc.
Inventor： Dingxian Wang , David Goldberg , Xiaoyuan Wu , Yuanjie Liu
IPC: G06F16/2457 , G06N20/00 , G06F16/2455 , G06Q10/06 , G06Q30/00
CPC classification number: G06F16/24578 , G06F16/2455 , G06N20/00 , G06Q10/06 , G06Q30/00
Abstract: A categorization analysis system is provided. The categorization analysis system includes one or more hardware processors, a memory including a first plurality of listings categorized in a first target category, and a categorization analysis engine executing on the one or more hardware processors. The categorization analysis engine is configured to determine a label for each listing including performing a search on title, select a set of training listings based on the determined labels, train a first model using the set of training listings and the determined labels, the first model being a classification model configured to classify categorization of listings, identify a suspect listing categorized in the first target category, apply the suspect listing to the first model, thereby generating a categorization result for the suspect listing, the categorization result indicating miscategorization of the suspect listing, and identify the suspect listing in the memory as miscategorized.
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公开(公告)号：US20210374150A1
公开(公告)日：2021-12-02
申请号：US17402034
申请日：2021-08-13
Applicant: eBay Inc.
Inventor： Dingxian Wang , David Goldberg , Xiaoyuan Wu , Yuanjie Liu
IPC: G06F16/2457 , G06N20/00 , G06F16/2455 , G06Q10/06 , G06Q30/00
Abstract: A categorization analysis system is provided. The categorization analysis system includes one or more hardware processors, a memory including a first plurality of listings categorized in a first target category, and a categorization analysis engine executing on the one or more hardware processors. The categorization analysis engine is configured to determine a label for each listing including performing a search on title, select a set of training listings based on the determined labels, train a first model using the set of training listings and the determined labels, the first model being a classification model configured to classify categorization of listings, identify a suspect listing categorized in the first target category, apply the suspect listing to the first model, thereby generating a categorization result for the suspect listing, the categorization result indicating miscategorization of the suspect listing, and identify the suspect listing in the memory as miscategorized.
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公开(公告)号：US11966440B2
公开(公告)日：2024-04-23
申请号：US17500455
申请日：2021-10-13
Applicant: eBay Inc.
Inventor： Dingxian Wang , Hongxu Chen , Guandong Xu , Li He
IPC: G06F16/70 , G06F16/74 , G06F16/78 , G06F16/783 , G06Q50/00
CPC classification number: G06F16/7867 , G06F16/743 , G06F16/7834 , G06F16/7844 , G06Q50/01
Abstract: A method for automatic metadata tag identification for videos is described. Content features are extracted from a video into respective data structures. The extracted content features are from at least two different feature modalities. The respective data structures are encoded into a common data structure using an encoder of a recurrent neural network (RNN) model. The common data structure is decoded using a decoder of the RNN model to identify content platform metadata tags to be associated with the video on a social content platform. Decoding is based on group tag data for users of the social content platform that identifies groups of the users and corresponding group metadata tags of interest for the groups of users.
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公开(公告)号：US20240054571A1
公开(公告)日：2024-02-15
申请号：US17818523
申请日：2022-08-09
Applicant: eBay Inc.
Inventor： Hongxu Chen , Li He , Dingxian Wang , Xianzhi Wang , Guangdong Xu , Haoran Yang
Abstract: Various embodiments include systems, methods, and non-transitory computer-readable media for identifying and matching influencers with categorized products using multimodal machine learning technologies. Consistent with these embodiments, a method includes identifying an influencer based on a set of criteria; determining a first attribute of the influencer based on context data associated with the influencer; identifying a second attribute of an item; generating a first vector that represents the first attribute of the influencer and a second vector that represents the second attribute of the item; generating a similarity score that represents a degree of similarity between the influencer and the item based on the first vector and the second vector; and causing display of the similarity score in a user interface of a device.
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Patent Agency Ranking
公开(公告)号：US11126631B2
公开(公告)日：2021-09-21
申请号：US15984059
申请日：2018-05-18
Applicant: eBay Inc.
Inventor： Dingxian Wang , David Goldberg , Xiaoyuan Wu , Yuanjie Liu
IPC: G06F16/2457 , G06N20/00 , G06F16/2455 , G06Q10/06 , G06Q30/00
Abstract: A categorization analysis system is provided. The categorization analysis system includes one or more hardware processors, a memory including a first plurality of listings categorized in a first target category, and a categorization analysis engine executing on the one or more hardware processors. The categorization analysis engine is configured to determine a label for each listing including performing a search on title, select a set of training listings based on the determined labels, train a first model using the set of training listings and the determined labels, the first model being a classification model configured to classify categorization of listings, identify a suspect listing categorized in the first target category, apply the suspect listing to the first model, thereby generating a categorization result for the suspect listing, the categorization result indicating miscategorization of the suspect listing, and identify the suspect listing in the memory as miscategorized.
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公开(公告)号：US12079227B2
公开(公告)日：2024-09-03
申请号：US18136867
申请日：2023-04-19
Applicant: eBay Inc.
Inventor： Dingxian Wang , David Goldberg , Xiaoyuan Wu , Yuanjie Liu
IPC: G06F16/2457 , G06F16/2455 , G06N20/00 , G06Q10/06 , G06Q30/00
CPC classification number: G06F16/24578 , G06F16/2455 , G06N20/00 , G06Q10/06 , G06Q30/00
Abstract: A categorization analysis system is provided. The categorization analysis system includes one or more hardware processors, a memory including a first plurality of listings categorized in a first target category, and a categorization analysis engine executing on the one or more hardware processors. The categorization analysis engine is configured to determine a label for each listing including performing a search on title, select a set of training listings based on the determined labels, train a first model using the set of training listings and the determined labels, the first model being a classification model configured to classify categorization of listings, identify a suspect listing categorized in the first target category, apply the suspect listing to the first model, thereby generating a categorization result for the suspect listing, the categorization result indicating miscategorization of the suspect listing, and identify the suspect listing in the memory as miscategorized.
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公开(公告)号：US20240220537A1
公开(公告)日：2024-07-04
申请号：US18607949
申请日：2024-03-18
Applicant: eBay Inc.
Inventor： Dingxian Wang , Hongxu Chen , Guandong Xu , Li He
IPC: G06F16/78 , G06F16/74 , G06F16/783 , G06Q50/00
CPC classification number: G06F16/7867 , G06F16/743 , G06F16/7834 , G06F16/7844 , G06Q50/01
Abstract: A method for automatic metadata tag identification for videos is described. Content features are extracted from a video into respective data structures. The extracted content features are from at least two different feature modalities. The respective data structures are encoded into a common data structure using an encoder of a recurrent neural network (RNN) model. The common data structure is decoded using a decoder of the RNN model to identify content platform metadata tags to be associated with the video on a social content platform. Decoding is based on group tag data for users of the social content platform that identifies groups of the users and corresponding group metadata tags of interest for the groups of users.
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公开(公告)号：US11875390B2
公开(公告)日：2024-01-16
申请号：US17088134
申请日：2020-11-03
Applicant: eBay Inc.
Inventor： Dingxian Wang
IPC: G06Q30/00 , G06Q30/0601 , G06F16/9538 , G06N5/025
CPC classification number: G06Q30/0627 , G06F16/9538 , G06N5/025 , G06Q30/0643
Abstract: Various embodiments improve search technologies and computer information retrieval by executing a query via ranking a set of search result candidates higher than another set search result candidates based at least in part on the query and determining that a first set of search result candidates are indicative of a sub-accessory to an accessory or an accessory itself.
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公开(公告)号：US20230252035A1
公开(公告)日：2023-08-10
申请号：US18136867
申请日：2023-04-19
Applicant: eBay Inc.
Inventor： Dingxian Wang , David Goldberg , Xiaoyuan Wu , Yuanjie Liu
IPC: G06F16/2457 , G06N20/00 , G06F16/2455 , G06Q10/06 , G06Q30/00
CPC classification number: G06F16/24578 , G06N20/00 , G06F16/2455 , G06Q10/06 , G06Q30/00
Abstract: A categorization analysis system is provided. The categorization analysis system includes one or more hardware processors, a memory including a first plurality of listings categorized in a first target category, and a categorization analysis engine executing on the one or more hardware processors. The categorization analysis engine is configured to determine a label for each listing including performing a search on title, select a set of training listings based on the determined labels, train a first model using the set of training listings and the determined labels, the first model being a classification model configured to classify categorization of listings, identify a suspect listing categorized in the first target category, apply the suspect listing to the first model, thereby generating a categorization result for the suspect listing, the categorization result indicating miscategorization of the suspect listing, and identify the suspect listing in the memory as miscategorized.
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