Patents by Inventor Erikas Bulba

Erikas Bulba 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).

  • Publication number: 20240028659
    Abstract: Systems and methods to intelligently optimize data collection requests are disclosed. In one embodiment, systems are configured to identify and select a complete set of suitable parameters to execute the data collection requests. In another embodiment, systems are configured to identify and select a partial set of suitable parameters to execute the data collection requests. The present embodiments can implement machine learning algorithms to identify and select the suitable parameters according to the nature of the data collection requests and the targets. Moreover, the embodiments provide systems and methods to generate feedback data based upon the effectiveness of the data collection parameters. Furthermore, the embodiments provide systems and methods to score the set of suitable parameters based on the feedback data and the overall cost, which are then stored in an internal database.
    Type: Application
    Filed: September 28, 2023
    Publication date: January 25, 2024
    Applicant: OXYLABS, UAB
    Inventors: MARTYNAS JURAVICIUS, ERIKAS BULBA, MANTAS BRILIAUSKAS
  • Patent number: 11809509
    Abstract: Systems and methods to intelligently optimize data collection requests are disclosed. In one embodiment, systems are configured to identify and select a complete set of suitable parameters to execute the data collection requests. In another embodiment, systems are configured to identify and select a partial set of suitable parameters to execute the data collection requests. The present embodiments can implement machine learning algorithms to identify and select the suitable parameters according to the nature of the data collection requests and the targets. Moreover, the embodiments provide systems and methods to generate feedback data based upon the effectiveness of the data collection parameters. Furthermore, the embodiments provide systems and methods to score the set of suitable parameters based on the feedback data and the overall cost, which are then stored in an internal database.
    Type: Grant
    Filed: March 10, 2023
    Date of Patent: November 7, 2023
    Assignee: OXYLABS, UAB
    Inventors: Martynas Juravicius, Erikas Bulba, Mantas Briliauskas
  • Publication number: 20230214436
    Abstract: Systems and methods to intelligently optimize data collection requests are disclosed. In one embodiment, systems are configured to identify and select a complete set of suitable parameters to execute the data collection requests. In another embodiment, systems are configured to identify and select a partial set of suitable parameters to execute the data collection requests. The present embodiments can implement machine learning algorithms to identify and select the suitable parameters according to the nature of the data collection requests and the targets. Moreover, the embodiments provide systems and methods to generate feedback data based upon the effectiveness of the data collection parameters. Furthermore, the embodiments provide systems and methods to score the set of suitable parameters based on the feedback data and the overall cost, which are then stored in an internal database.
    Type: Application
    Filed: March 10, 2023
    Publication date: July 6, 2023
    Applicant: OXYLABS, UAB
    Inventors: MARTYNAS JURAVICIUS, ERIKAS BULBA, MANTAS BRILIAUSKAS
  • Patent number: 11636169
    Abstract: Systems and methods to intelligently optimize data collection requests are disclosed. In one embodiment, systems are configured to identify and select a complete set of suitable parameters to execute the data collection requests. In another embodiment, systems are configured to identify and select a partial set of suitable parameters to execute the data collection requests. The present embodiments can implement machine learning algorithms to identify and select the suitable parameters according to the nature of the data collection requests and the targets. Moreover, the embodiments provide systems and methods to generate feedback data based upon the effectiveness of the data collection parameters. Furthermore, the embodiments provide systems and methods to score the set of suitable parameters based on the feedback data and the overall cost, which are then stored in an internal database.
    Type: Grant
    Filed: August 31, 2022
    Date of Patent: April 25, 2023
    Assignee: Oxylabs, UAB
    Inventors: Martynas Juravicius, Erikas Bulba, Mantas Briliauskas
  • Publication number: 20230066328
    Abstract: Systems and methods to intelligently optimize data collection requests are disclosed. In one embodiment, systems are configured to identify and select a complete set of suitable parameters to execute the data collection requests. In another embodiment, systems are configured to identify and select a partial set of suitable parameters to execute the data collection requests. The present embodiments can implement machine learning algorithms to identify and select the suitable parameters according to the nature of the data collection requests and the targets. Moreover, the embodiments provide systems and methods to generate feedback data based upon the effectiveness of the data collection parameters. Furthermore, the embodiments provide systems and methods to score the set of suitable parameters based on the feedback data and the overall cost, which are then stored in an internal database.
    Type: Application
    Filed: August 31, 2022
    Publication date: March 2, 2023
    Applicant: METACLUSTER LT, UAB
    Inventors: MARTYNAS JURAVICIUS, ERIKAS BULBA, MANTAS BRILIAUSKAS
  • Patent number: 11468137
    Abstract: Systems and methods to intelligently optimize data collection requests are disclosed. In one embodiment, systems are configured to identify and select a complete set of suitable parameters to execute the data collection requests. In another embodiment, systems are configured to identify and select a partial set of suitable parameters to execute the data collection requests. The present embodiments can implement machine learning algorithms to identify and select the suitable parameters according to the nature of the data collection requests and the targets. Moreover, the embodiments provide systems and methods to generate feedback data based upon the effectiveness of the data collection parameters. Furthermore, the embodiments provide systems and methods to score the set of suitable parameters based on the feedback data and the overall cost, which are then stored in an internal database.
    Type: Grant
    Filed: March 22, 2022
    Date of Patent: October 11, 2022
    Assignee: METACLUSTER LT, UAB
    Inventors: Martynas Juravicius, Erikas Bulba, Mantas Briliauskas
  • Patent number: 11314833
    Abstract: Systems and methods to intelligently optimize data collection requests are disclosed. In one embodiment, systems are configured to identify and select a complete set of suitable parameters to execute the data collection requests. In another embodiment, systems are configured to identify and select a partial set of suitable parameters to execute the data collection requests. The present embodiments can implement machine learning algorithms to identify and select the suitable parameters according to the nature of the data collection requests and the targets. Moreover, the embodiments provide systems and methods to generate feedback data based upon the effectiveness of the data collection parameters. Furthermore, the embodiments provide systems and methods to score the set of suitable parameters based on the feedback data and the overall cost, which are then stored in an internal database.
    Type: Grant
    Filed: November 9, 2021
    Date of Patent: April 26, 2022
    Assignee: METACLUSTER LT, UAB
    Inventors: Martynas Juravicius, Erikas Bulba, Mantas Briliauskas