Patents by Inventor Karin Steckler

Karin Steckler 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: 11687574
    Abstract: A computer implemented method comprising processing the unstructured objects of each record of records of a database for identifying a set of one or more values of attributes in the unstructured objects of the each record. The sets of unstructured attribute values of two records of the database may be compared for determining a similarity level between the two sets. It may be determined whether the two records are representing a same entity based on the comparison result.
    Type: Grant
    Filed: March 29, 2021
    Date of Patent: June 27, 2023
    Assignee: International Business Machines Corporation
    Inventors: Lars Bremer, Martin Oberhofer, Karin Steckler, Mariya Chkalova, Michael Baessler, Holger Koenig
  • Publication number: 20230185941
    Abstract: A computer-implemented method for managing data records subject to placement condition rules in a distributed data management system comprising a plurality of nodes. The method may include receiving, by an endpoint management component of the distributed data management system, a request for a data record. The method may also include routing, by the endpoint management component of the distributed data management system, the request to a node of the distributed data management system. The method may also include upon determining that the request is a create request, verifying, by a service component of the distributed data management system, a placement condition rule for the data record, where the placement condition rule is retrieved from a configuration component of the distributed data management system.
    Type: Application
    Filed: December 14, 2021
    Publication date: June 15, 2023
    Inventors: Martin Anton Oberhofer, Oliver Suhre, Sergej Schuetz, Theresa Schmitt, Karin Steckler, Hemanth Kumar Babu
  • Publication number: 20230110792
    Abstract: A system including a processor and a memory storing program instructions and a machine learning module. The machine learning module is configured for outputting one or more suggested data element change requests in response to receiving an initial data element change request. Execution of the program instructions causes the processor to receive the initial data element change request, receive the one or more suggested data element change requests in response to inputting the initial data element change request into the machine learning module, receive one or more subsequent data element change requests, detect if the one or more subsequent data element change requests contain the one or more suggested data element change requests, and provide an alert signal if the one or more suggested data element change requests are not detected within the one or more subsequent data element change requests.
    Type: Application
    Filed: October 8, 2021
    Publication date: April 13, 2023
    Inventors: Lars Bremer, Martin Anton Oberhofer, Karin Steckler, Holger Koenig, Mariya Chkalova
  • Publication number: 20220309084
    Abstract: A computer implemented method comprising processing the unstructured objects of each record of records of a database for identifying a set of one or more values of attributes in the unstructured objects of the each record. The sets of unstructured attribute values of two records of the database may be compared for determining a similarity level between the two sets. It may be determined whether the two records are representing a same entity based on the comparison result.
    Type: Application
    Filed: March 29, 2021
    Publication date: September 29, 2022
    Inventors: Lars Bremer, Martin Oberhofer, Karin Steckler, Mariya Chkalova, Michael Baessler, Holger Koenig
  • Publication number: 20220215286
    Abstract: A method, computer system, and computer program product for training a machine learning model for use by a task management system are provided. The embodiment may include presenting a task to be resolved to a user via a user interface. The embodiment may also include presenting a further task to be resolved to the user via the user interface. The embodiment may further include predicting time to be spent on the further task presented to the user. The embodiment may also include determining actual time the user spent completing the further task. The embodiment may further include training a machine learning model for a subsequent similar task based on the predicted time and the determined actual time.
    Type: Application
    Filed: January 4, 2021
    Publication date: July 7, 2022
    Inventors: Alexandre Luz Xavier Da Costa, Lars Bremer, Karin Steckler, Thuany Karoline Stuart
  • Publication number: 20210374525
    Abstract: The present disclosure relates to a method comprising providing a set of one or more records, each record of the set of records having a set of one or more attributes. Values of the set of attributes of the set of records may be input to a trained data representation learning model for receiving, as an output of the trained data representation model, a set of feature vectors representing the set of records respectively. The set of feature vectors may be stored.
    Type: Application
    Filed: December 9, 2020
    Publication date: December 2, 2021
    Inventors: Lars Bremer, Jonathan Roesner, Claudio Andrea Fanconi, Martin Oberhofer, Karin Steckler