Patents by Inventor Chenyi Li

Chenyi Li 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: 20250058379
    Abstract: The present application provides a preparation method for iridium nanocrystal, including the following steps: mixing an iridium salt, an alcohol solvent and a centrifugal waste liquid to form a mixed solution, and adding an alkali solution in an inert atmosphere for a heating reaction. After centrifugation, an iridium nanocrystal is obtained. The centrifugal waste liquid is a waste liquid produced in the pre-synthesis process of iridium nanocrystal. The preparation method can shorten the reaction time, and the obtained iridium nanocrystal has the advantages of high yield and low cost.
    Type: Application
    Filed: November 5, 2024
    Publication date: February 20, 2025
    Inventors: Yanfei WANG, Yinglong YU, Chenyi SHAO, Chuan LONG, Qinfeng ZHAO, Jingjing WANG, Yeheng HE, Qingxun LI
  • Publication number: 20250053564
    Abstract: System and methods are presented for associating a user-posted content item with an interest node of an interest taxonomy. A corpus of content items and an interest taxonomy are maintained. The interest taxonomy comprises interest nodes organized in a hierarchical organization, each node having a text label descriptive of the interest node. Additionally, the content items of the corpus are associated with one or more interest nodes of the interest taxonomy. Upon receiving a user-posted content item, feature sets of the received content item are generated, these feature sets based on features and/or aspects of the received content item. After generating at least one feature set, the at least one feature set is provided to an interest prediction model that generates candidate interest nodes for the user-posted content item. At least some of the candidate interest nodes are associated with the user-posted content item in the corpus.
    Type: Application
    Filed: October 30, 2024
    Publication date: February 13, 2025
    Applicant: Pinterest, Inc.
    Inventors: Chenyi Li, Yunsong Guo, Yu Liu
  • Publication number: 20250037113
    Abstract: The present disclosure provides a method for opening a digital wallet, a wallet application terminal, and a system. The method comprises: acquiring, from a digital currency issuer agency server, a list of operating agency servers that can open a digital wallet and displaying the list of operating agency servers, so that a user selects a target operating agency server from the list of operating agency servers; communicating with the target operating agency server, so that the target operating agency server verifies the user; when the verification is passed, sending a digital wallet opening request to the digital currency issuer agency server, so that the digital currency issuer agency server notifies the target operating agency server to perform a digital wallet opening operation, or sending a digital wallet opening request to the target operating agency server, so that the target operating agency server performs a digital wallet opening operation.
    Type: Application
    Filed: July 22, 2022
    Publication date: January 30, 2025
    Inventors: Zhuo CHENG, Guangyao LI, Chenyi PENG
  • Patent number: 12153583
    Abstract: System and methods are presented for associating a user-posted content item with an interest node of an interest taxonomy. A corpus of content items and an interest taxonomy are maintained. The interest taxonomy comprises interest nodes organized in a hierarchical organization, each node having a text label descriptive of the interest node. Additionally, the content items of the corpus are associated with one or more interest nodes of the interest taxonomy. Upon receiving a user-posted content item, feature sets of the received content item are generated, these feature sets based on features and/or aspects of the received content item. After generating at least one feature set, the at least one feature set is provided to an interest prediction model that generates candidate interest nodes for the user-posted content item. At least some of the candidate interest nodes are associated with the user-posted content item in the corpus.
    Type: Grant
    Filed: September 20, 2019
    Date of Patent: November 26, 2024
    Assignee: Pinterest, Inc.
    Inventors: Chenyi Li, Yunsong Guo, Yu Liu
  • Publication number: 20240211698
    Abstract: Systems and methods are presented for inferring an embedding vector of an item of a first type into the embedding space. Upon receiving a first time for which there is no embedding vector, documents of a document corpus that include (co-occurrence) both the received item and other items of the same type are identified. Of those other items that have embedding vectors, those embedding vectors are retrieved and averaged. The resulting averaged embedding vector is established as an inferred embedding vector for the received item.
    Type: Application
    Filed: March 4, 2024
    Publication date: June 27, 2024
    Applicant: Pinterest, Inc.
    Inventors: Heath Vinicombe, Chenyi Li, Yunsong Guo, Yu Liu
  • Patent number: 11960846
    Abstract: Systems and methods are presented for inferring an embedding vector of an item of a first type into the embedding space. Upon receiving a first time for which there is no embedding vector, documents of a document corpus that include (co-occurrence) both the received item and other items of the same type are identified. Of those other items that have embedding vectors, those embedding vectors are retrieved and averaged. The resulting averaged embedding vector is established as an inferred embedding vector for the received item.
    Type: Grant
    Filed: May 10, 2023
    Date of Patent: April 16, 2024
    Assignee: Pinterest, Inc.
    Inventors: Heath Vinicombe, Chenyi Li, Yunsong Guo, Yu Liu
  • Patent number: 11797775
    Abstract: Systems and methods are presented for inferring an embedding vector of an item of a first type into the embedding space. Upon receiving a first time for which there is no embedding vector, documents of a document corpus that include (co-occurrence) both the received item and other items of the same type are identified. Of those other items that have embedding vectors, those embedding vectors are retrieved and averaged. The resulting averaged embedding vector is established as an inferred embedding vector for the received item.
    Type: Grant
    Filed: September 12, 2019
    Date of Patent: October 24, 2023
    Assignee: Pinterest, Inc.
    Inventors: Heath Vinicombe, Chenyi Li, Yunsong Guo, Yu Liu
  • Publication number: 20230281395
    Abstract: Systems and methods are presented for inferring an embedding vector of an item of a first type into the embedding space. Upon receiving a first time for which there is no embedding vector, documents of a document corpus that include (co-occurrence) both the received item and other items of the same type are identified. Of those other items that have embedding vectors, those embedding vectors are retrieved and averaged. The resulting averaged embedding vector is established as an inferred embedding vector for the received item.
    Type: Application
    Filed: May 10, 2023
    Publication date: September 7, 2023
    Applicant: Pinterest, Inc.
    Inventors: Heath Vinicombe, Chenyi Li, Yunsong Guo, Yu Liu
  • Publication number: 20210089539
    Abstract: System and methods are presented for associating a user-posted content item with an interest node of an interest taxonomy. A corpus of content items and an interest taxonomy are maintained. The interest taxonomy comprises interest nodes organized in a hierarchical organization, each node having a text label descriptive of the interest node. Additionally, the content items of the corpus are associated with one or more interest nodes of the interest taxonomy. Upon receiving a user-posted content item, feature sets of the received content item are generated, these feature sets based on features and/or aspects of the received content item. After generating at least one feature set, the at least one feature set is provided to an interest prediction model that generates candidate interest nodes for the user-posted content item. At least some of the candidate interest nodes are associated with the user-posted content item in the corpus.
    Type: Application
    Filed: September 20, 2019
    Publication date: March 25, 2021
    Inventors: Chenyi Li, Yunsong Guo, Yu Liu