Patents by Inventor Tala El Hallak

Tala El Hallak 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: 11397754
    Abstract: Techniques for context-based keyword grouping for business rule mining are described herein. An aspect includes determining, based on a first corpus, a first list of keywords. Another aspect includes constructing a co-occurrence matrix based on the first list of keywords. Another aspect includes applying a clustering algorithm to the co-occurrence matrix to determine a first plurality of keyword groups. Another aspect includes presenting the first plurality of keyword groups to a user via a user interface.
    Type: Grant
    Filed: February 14, 2020
    Date of Patent: July 26, 2022
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Yan Luo, Rahamim Katan, Gary Mazo, Monvorath Phongpaibul, Tala El Hallak, Stanislav Georgiev, Hongxia Li
  • Patent number: 11163833
    Abstract: Aspects include a method for generating an initial ranking of a plurality of discovered keywords, in which the initial ranking is based on confidence levels. The method includes presenting the initial ranking to a user as a list that includes the plurality of discovered keywords. The method includes, in response to receiving a text string as a first input from the user, filtering the list of discovered keywords to generate a refined list of discovered keywords. The filtering includes searching the list of discovered keywords to rank keywords that match the input string using a fuzzy search. The method includes mapping a discovered keyword of the refined list to a business term using a fuzzy search. The method includes updating the initial ranking based on the mapping of the discovered keyword.
    Type: Grant
    Filed: September 6, 2018
    Date of Patent: November 2, 2021
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Peter Haumer, William J. Scheid, III, Stanislav Georgiev, Yan Luo, Tala El Hallak
  • Publication number: 20210256036
    Abstract: Techniques for context-based keyword grouping for business rule mining are described herein. An aspect includes determining, based on a first corpus, a first list of keywords. Another aspect includes constructing a co-occurrence matrix based on the first list of keywords. Another aspect includes applying a clustering algorithm to the co-occurrence matrix to determine a first plurality of keyword groups. Another aspect includes presenting the first plurality of keyword groups to a user via a user interface.
    Type: Application
    Filed: February 14, 2020
    Publication date: August 19, 2021
    Inventors: Yan Luo, Rahamim Katan, Gary Mazo, Monvorath Phongpaibul, Tala El Hallak, Stanislav Georgiev, Hongxia Li
  • Publication number: 20200082027
    Abstract: Provided are systems, methods, and media for discovering and displaying business artifact and term relationships. An example method includes generating an initial ranking of a plurality of discovered keywords, in which the initial ranking is based on confidence levels. The method includes presenting the initial ranking to a user as a list comprising the plurality of discovered keywords. The method includes, in response to receiving a text string as a first input from the user, filtering the list of discovered keywords to generate a refined list of discovered keywords, in which the filtering includes searching the list of discovered keywords to rank keywords that match the input string using a fuzzy search. The method includes mapping a discovered keyword of the refined list to a business term using a fuzzy search. The method includes updating the initial ranking based on the mapping of the discovered keyword.
    Type: Application
    Filed: September 6, 2018
    Publication date: March 12, 2020
    Inventors: Peter Haumer, William J. Scheid, III, Stanislav Georgiev, Yan Luo, Tala El Hallak