Patents by Inventor Jyun-Tang Huang

Jyun-Tang Huang 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).

  • Patent number: 10572929
    Abstract: A decision factors analyzing device and a decision factors analyzing device for analyzing a plurality of decision factors which cause a product of a product type to be purchased are provided. The method includes identifying a plurality of product sequences corresponding to the product type from a plurality of browse history data and a plurality of purchase history data corresponding to a plurality of consumers of a consumer database, wherein each of the product sequences includes a unpurchased product and a purchased product; obtaining a feature sequence according to the produce sequences and a plurality of product information; training a regression model corresponding to the product type according to K decision factors of the feature sequence to obtain an optimized regression model, and obtaining K decision values respectively corresponding to the K decision factors according to the optimized regression model to generate a decision factor sequence corresponding to the product type.
    Type: Grant
    Filed: December 25, 2017
    Date of Patent: February 25, 2020
    Assignee: Industrial Technology Research Institute
    Inventors: Cheng-Liang Lin, Jie-Sin Li, En-Tzu Wang, Jyun-Tang Huang, Tsung-Wen Tso
  • Publication number: 20190164213
    Abstract: A decision factors analyzing device and a decision factors analyzing device for analyzing a plurality of decision factors which cause a product of a product type to be purchased are provided. The method includes identifying a plurality of product sequences corresponding to the product type from a plurality of browse history data and a plurality of purchase history data corresponding to a plurality of consumers of a consumer database, wherein each of the product sequences includes a unpurchased product and a purchased product; obtaining a feature sequence according to the produce sequences and a plurality of product information; training a regression model corresponding to the product type according to K decision factors of the feature sequence to obtain an optimized regression model, and obtaining K decision values respectively corresponding to the K decision factors according to the optimized regression model to generate a decision factor sequence corresponding to the product type.
    Type: Application
    Filed: December 25, 2017
    Publication date: May 30, 2019
    Applicant: Industrial Technology Research Institute
    Inventors: Cheng-Liang Lin, Jie-Sin Li, En-Tzu Wang, Jyun-Tang Huang, Tsung-Wen Tso