Patents by Inventor Dingxian Wang

Dingxian Wang has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20240380822
    Abstract: One of the important signals that online platforms rely upon is the click-through rate prediction. This allows a platform, such as a video platform, to provide items, such as videos, to users based on how likely the user is to interact with the item. A hypergraph model is provided to exploit the temporal user-item interactions to guide the representation learning with multi-modal features, and further predict the user click-through rate of an item. The hypergraph model is built upon the hyperedge notion of hypergraph neural networks. In this way, item modalities, such as visual, acoustic, and textual aspects can be used to enhance the click-through rate prediction and, thus, enhance the likelihood that the online platform will provide relevant content. The technology leverages hypergraphs, including interest-based hypergraphs and item hypergraphs that uniquely provide the relationship between user and items. The hypergraph model described demonstrably outperforms various state-of-the-art methods.
    Type: Application
    Filed: August 26, 2021
    Publication date: November 14, 2024
    Inventors: Dingxian WANG, Guandong XU, Hongxu CHEN, Li HE
  • Publication number: 20240346604
    Abstract: Technologies are shown for mapping micro-video hashtags to content categories that involve collecting content categories from a content service, collecting micro-video, hashtags and user interaction semantic data from a micro-video service, determining a correlation of a content category to the micro-video, hashtags and user interaction semantic data using a multi-layer graph convolution network, and providing the hashtags correlated with the content category to the content service. The correlation can be determined by processing the semantic data with a concatenation layer and a full connected layer to produce a user-specific micro-video and hashtag representations. Similarity scores for determining correlation can be calculated from category content and a dot product of the representations.
    Type: Application
    Filed: August 13, 2021
    Publication date: October 17, 2024
    Inventors: Dingxian WANG, Guandong XU, Hongxu CHEN, Li HE
  • Patent number: 12079227
    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.
    Type: Grant
    Filed: April 19, 2023
    Date of Patent: September 3, 2024
    Assignee: EBAY INC.
    Inventors: Dingxian Wang, David Goldberg, Xiaoyuan Wu, Yuanjie Liu
  • Publication number: 20240220537
    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.
    Type: Application
    Filed: March 18, 2024
    Publication date: July 4, 2024
    Applicant: eBay Inc.
    Inventors: Dingxian Wang, Hongxu Chen, Guandong Xu, Li He
  • Patent number: 11966440
    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.
    Type: Grant
    Filed: October 13, 2021
    Date of Patent: April 23, 2024
    Assignee: eBay Inc.
    Inventors: Dingxian Wang, Hongxu Chen, Guandong Xu, Li He
  • Publication number: 20240104621
    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.
    Type: Application
    Filed: December 1, 2023
    Publication date: March 28, 2024
    Inventor: Dingxian WANG
  • Publication number: 20240054571
    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.
    Type: Application
    Filed: August 9, 2022
    Publication date: February 15, 2024
    Inventors: Hongxu Chen, Li He, Dingxian Wang, Xianzhi Wang, Guangdong Xu, Haoran Yang
  • Patent number: 11875390
    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.
    Type: Grant
    Filed: November 3, 2020
    Date of Patent: January 16, 2024
    Assignee: eBay Inc.
    Inventor: Dingxian Wang
  • Publication number: 20230252035
    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.
    Type: Application
    Filed: April 19, 2023
    Publication date: August 10, 2023
    Inventors: Dingxian Wang, David Goldberg, Xiaoyuan Wu, Yuanjie Liu
  • Patent number: 11663225
    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.
    Type: Grant
    Filed: August 13, 2021
    Date of Patent: May 30, 2023
    Assignee: eBay Inc.
    Inventors: Dingxian Wang, David Goldberg, Xiaoyuan Wu, Yuanjie Liu
  • Publication number: 20230115897
    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.
    Type: Application
    Filed: October 13, 2021
    Publication date: April 13, 2023
    Applicant: eBay Inc.
    Inventors: Dingxian WANG, Hongxu CHEN, Guandong XU, Li HE
  • Publication number: 20220138826
    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.
    Type: Application
    Filed: November 3, 2020
    Publication date: May 5, 2022
    Inventor: Dingxian Wang
  • Publication number: 20210374150
    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.
    Type: Application
    Filed: August 13, 2021
    Publication date: December 2, 2021
    Inventors: Dingxian Wang, David Goldberg, Xiaoyuan Wu, Yuanjie Liu
  • Patent number: 11126631
    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.
    Type: Grant
    Filed: May 18, 2018
    Date of Patent: September 21, 2021
    Assignee: eBay Inc.
    Inventors: Dingxian Wang, David Goldberg, Xiaoyuan Wu, Yuanjie Liu
  • Publication number: 20180329913
    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.
    Type: Application
    Filed: May 18, 2018
    Publication date: November 15, 2018
    Inventors: Dingxian Wang, David Goldberg, Xiaoyuan Wu, Yuanjie Liu
  • Patent number: 9996590
    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.
    Type: Grant
    Filed: December 31, 2015
    Date of Patent: June 12, 2018
    Assignee: eBay Inc.
    Inventors: Dingxian Wang, David Goldberg, Xiaoyuan Wu, Yuanjie Liu
  • Publication number: 20170192975
    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.
    Type: Application
    Filed: December 31, 2015
    Publication date: July 6, 2017
    Inventors: Dingxian Wang, David Goldberg, Xiaoyuan Wu, Yuanjie Liu