Patents by Inventor Chi Kam P. Yau

Chi Kam P. Yau 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).

  • Matching customer and product behavioral traits
    Patent number: 11295366
    Abstract: At least one detail for at least one product in a group of products is received. At least one input for at least one customer in a group of customers is received. At least one detail for at least one product and at least one input for at least one customer is stored to a database repository. Product traits for at least one product are generated and stored to a database repository. Customer traits for at least one customer are generated and stored to a database repository. The generation of customer traits is independent from the generation of product traits. At least one recommendation for matching at least one product to at least one customer is generated. The at least one recommendation is based on the generated traits of the at least one product and the generated traits of the at least one customer.
    Type: Grant
    Filed: August 22, 2019
    Date of Patent: April 5, 2022
    Assignee: International Business Machines Corporation
    Inventors: Alan M. E. Leong, Shaun N. Maharaj, Parnit Pooni, Chi Kam P. Yau
  • Automated product personalization based on mulitple sources of product information
    Patent number: 10607277
    Abstract: In an approach to customer-product matching, a computing device receives textual information related to a product. The computing device generates a set of product personality traits based on analyzing the textual information by a natural language processor. The computing device identifies a set of customer personality traits for a target customer group. The computing device determines whether a degree of correlation between a first trait from the set of product personality traits and a second trait from the set of customer personality traits meets or exceeds a predetermined threshold value. Responsive to determining that the degree of correlation does not meet or exceed a predetermined threshold value, the computing device revises the textual information based on a psycholinguistic dictionary. The computing device continues to revise the set of product personality traits until the degree of correlation meets or exceeds the predetermined threshold value.
    Type: Grant
    Filed: February 23, 2016
    Date of Patent: March 31, 2020
    Assignee: International Business Machines Corporation
    Inventors: Alan M. E. Leong, Shaun N. Maharaj, Parnit Pooni, Chi Kam P. Yau
  • MATCHING CUSTOMER AND PRODUCT BEHAVIORAL TRAITS
    Publication number: 20190378197
    Abstract: At least one detail for at least one product in a group of products is received. At least one input for at least one customer in a group of customers is received. At least one detail for at least one product and at least one input for at least one customer is stored to a database repository. Product traits for at least one product are generated and stored to a database repository. Customer traits for at least one customer are generated and stored to a database repository. The generation of customer traits is independent from the generation of product traits. At least one recommendation for matching at least one product to at least one customer is generated. The at least one recommendation is based on the generated traits of the at least one product and the generated traits of the at least one customer.
    Type: Application
    Filed: August 22, 2019
    Publication date: December 12, 2019
    Inventors: Alan M.E. Leong, Shaun N. Maharaj, Parnit Pooni, Chi Kam P. Yau
  • AUTOMATED PRODUCT PERSONALIZATION BASED ON MULTIPLE SOURCES OF PRODUCT INFORMATION
    Publication number: 20180047095
    Abstract: In an approach to customer-product matching, a computing device receives textual information related to a product. The computing device generates a set of product personality traits based on analyzing the textual information by a natural language processor. The computing device identifies a set of customer personality traits for a target customer group. The computing device determines whether a degree of correlation between a first trait from the set of product personality traits and a second trait from the set of customer personality traits meets or exceeds a predetermined threshold value. Responsive to determining that the degree of correlation does not meet or exceed a predetermined threshold value, the computing device revises the textual information based on a psycholinguistic dictionary. The computing device continues to revise the set of product personality traits until the degree of correlation meets or exceeds the predetermined threshold value.
    Type: Application
    Filed: October 27, 2017
    Publication date: February 15, 2018
    Inventors: Alan M.E. Leong, Shaun N. Maharaj, Parnit Pooni, Chi Kam P. Yau
  • AUTOMATED PRODUCT PERSONALIZATION BASED ON MULITPLE SOURCES OF PRODUCT INFORMATION
    Publication number: 20170243281
    Abstract: In an approach to customer-product matching, a computing device receives textual information related to a product. The computing device generates a set of product personality traits based on analyzing the textual information by a natural language processor. The computing device identifies a set of customer personality traits for a target customer group. The computing device determines whether a degree of correlation between a first trait from the set of product personality traits and a second trait from the set of customer personality traits meets or exceeds a predetermined threshold value. Responsive to determining that the degree of correlation does not meet or exceed a predetermined threshold value, the computing device revises the textual information based on a psycholinguistic dictionary. The computing device continues to revise the set of product personality traits until the degree of correlation meets or exceeds the predetermined threshold value.
    Type: Application
    Filed: February 23, 2016
    Publication date: August 24, 2017
    Inventors: Alan M.E. Leong, Shaun N. Maharaj, Parnit Pooni, Chi Kam P. Yau
  • MATCHING CUSTOMER AND PRODUCT BEHAVIORAL TRAITS
    Publication number: 20170221126
    Abstract: At least one detail for at least one product in a group of products is received. At least one input for at least one customer in a group of customers is received. At least one detail for at least one product and at least one input for at least one customer is stored to a database repository. Product traits for at least one product are generated and stored to a database repository. Customer traits for at least one customer are generated and stored to a database repository. The generation of customer traits is independent from the generation of product traits. At least one recommendation for matching at least one product to at least one customer is generated. The at least one recommendation is based on the generated traits of the at least one product and the generated traits of the at least one customer.
    Type: Application
    Filed: April 4, 2016
    Publication date: August 3, 2017
    Inventors: Alan M.E. Leong, Shaun N. Maharaj, Parnit Pooni, Chi Kam P. Yau
  • MATCHING CUSTOMER AND PRODUCT BEHAVIORAL TRAITS
    Publication number: 20170221125
    Abstract: At least one detail for at least one product in a group of products is received. At least one input for at least one customer in a group of customers is received. At least one detail for at least one product and at least one input for at least one customer is stored to a database repository. Product traits for at least one product are generated and stored to a database repository. Customer traits for at least one customer are generated and stored to a database repository. The generation of customer traits is independent from the generation of product traits. At least one recommendation for matching at least one product to at least one customer is generated. The at least one recommendation is based on the generated traits of the at least one product and the generated traits of the at least one customer.
    Type: Application
    Filed: February 3, 2016
    Publication date: August 3, 2017
    Inventors: Alan M.E. Leong, Shaun N. Maharaj, Parnit Pooni, Chi Kam P. Yau