Patents by Inventor Liu Wenyin

Liu Wenyin 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).

  • Statistical bigram correlation model for image retrieval
    Patent number: 7430566
    Abstract: The disclosed subject matter improves iterative results of content-based image retrieval (CBIR) using a bigram model to correlate relevance feedback. Specifically, multiple images are received responsive to multiple image search sessions. Relevance feedback is used to determine whether the received images are semantically relevant. A respective semantic correlation between each of at least one pair of the images is then estimated using respective bigram frequencies. The bigram frequencies are based on multiple search sessions in which each image of a pair of images is semantically relevant.
    Type: Grant
    Filed: February 11, 2005
    Date of Patent: September 30, 2008
    Assignee: Microsoft Corporation
    Inventors: Mingjing Li, Zheng Chen, Liu Wenyin, Hong-Jiang Zhang
  • User intention modeling for web navigation
    Patent number: 6993586
    Abstract: The disclosed subject matter models or predicts a user's intention during network or WWW navigation. Specifically, a statistical multi-step n-gram probability model is used to predict a user's optimal information goal. The optimal information goal is based on a sequence of previously visited network content pieces and a globally optimized navigation path through the sequence.
    Type: Grant
    Filed: May 9, 2002
    Date of Patent: January 31, 2006
    Assignee: Microsoft Corporation
    Inventors: Zheng Chen, Xiaoming Sun, Liu Wenyin
  • User intention modeling for web navigation
    Publication number: 20060010229
    Abstract: The disclosed subject matter models or predicts a user's intention during network or WWW navigation. Specifically, a statistical multi-step n-gram probability model is used to predict a user's optimal information goal. The optimal information goal is based on a sequence of previously visited network content pieces and a globally optimized navigation path through the sequence.
    Type: Application
    Filed: September 6, 2005
    Publication date: January 12, 2006
    Applicant: Microsoft Corporation
    Inventors: Zheng Chen, Xiaoming Sun, Liu Wenyin
  • Statistical bigram correlation model for image retrieval
    Publication number: 20050165763
    Abstract: The disclosed subject matter improves iterative results of content-based image retrieval (CBIR) using a bigram model to correlate relevance feedback. Specifically, multiple images are received responsive to multiple image search sessions. Relevance feedback is used to determine whether the received images are semantically relevant. A respective semantic correlation between each of at least one pair of the images is then estimated using respective bigram frequencies. The bigram frequencies are based on multiple search sessions in which each image of a pair of images is semantically relevant.
    Type: Application
    Filed: February 11, 2005
    Publication date: July 28, 2005
    Applicant: Microsoft Corporation
    Inventors: Mingjing Li, Zheng Chen, Liu Wenyin, Hong-Jiang Zhang
  • Statistical bigram correlation model for image retrieval
    Patent number: 6901411
    Abstract: The disclosed subject matter improves iterative results of content-based image retrieval (CBIR) using a bigram model to correlate relevance feedback. Specifically, multiple images are received responsive to multiple image search sessions. Relevance feedback is used to determine whether the received images are semantically relevant. A respective semantic correlation between each of at least one pair of the images is then estimated using respective bigram frequencies. The bigram frequencies are based on multiple search sessions in which each image of a pair of images is semantically relevant.
    Type: Grant
    Filed: February 11, 2002
    Date of Patent: May 31, 2005
    Assignee: Microsoft Corporation
    Inventors: Mingjing Li, Zheng Chen, Liu Wenyin, Hong-Jiang Zhang
  • User Intention modeling for Web navigation
    Publication number: 20030212760
    Abstract: The disclosed subject matter models or predicts a user's intention during network or WWW navigation. Specifically, a statistical multi-step n-gram probability model is used to predict a user's optimal information goal. The optimal information goal is based on a sequence of previously visited network content pieces and a globally optimized navigation path through the sequence.
    Type: Application
    Filed: May 9, 2002
    Publication date: November 13, 2003
    Inventors: Zheng Chen, Xiaoming Sun, Liu Wenyin
  • Statistical bigram correlation model for image retrieval
    Publication number: 20030187844
    Abstract: The disclosed subject matter improves iterative results of content-based image retrieval (CBIR) using a bigram model to correlate relevance feedback. Specifically, multiple images are received responsive to multiple image search sessions. Relevance feedback is used to determine whether the received images are semantically relevant. A respective semantic correlation between each of at least one pair of the images is then estimated using respective bigram frequencies. The bigram frequencies are based on multiple search sessions in which each image of a pair of images is semantically relevant.
    Type: Application
    Filed: February 11, 2002
    Publication date: October 2, 2003
    Inventors: Mingjing Li, Zheng Chen, Liu Wenyin, Hong-Jiang Zhang