Patents by Inventor CRAIG GASKILL
CRAIG GASKILL 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).
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Publication number: 20240095490Abstract: Aspect pre-selection techniques using machine learning are described. In one example, an artificial assistant system is configured to implement a chat bot. A user then engages in a first natural-language conversation. As part of this first natural-language conversation, a communication is generated by the chat bot to prompt the user to specify an aspect of a category that is a subject of a first natural-language conversation and user data is received in response. Data that describes this first natural-language conversation is used to train a model using machine learning. Data is then received by the chat bot as part of a second natural-language conversation. This data, from the second natural-language conversation, is processed using the model as part of machine learning to generate the second search query to include the aspect of the category automatically and without user intervention.Type: ApplicationFiled: November 29, 2023Publication date: March 21, 2024Applicant: eBay Inc.Inventors: Farah Abdallah, Robert Enyedi, Amit Srivastava, Elaine Lee, Braddock Craig Gaskill, Tomer Lancewicki, Xinyu Zhang, Jayanth Vasudevan, Dominique Jean Bouchon
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Patent number: 11875241Abstract: Aspect pre-selection techniques using machine learning are described. In one example, an artificial assistant system is configured to implement a chat bot. A user then engages in a first natural-language conversation. As part of this first natural-language conversation, a communication is generated by the chat bot to prompt the user to specify an aspect of a category that is a subject of a first natural-language conversation and user data is received in response. Data that describes this first natural-language conversation is used to train a model using machine learning. Data, is then be received by the chat bot as part of a second natural-language conversation. This data, from the second natural-language conversation, is processed using the model as part of machine learning to generate the second search query to include the aspect of the category automatically and without user intervention.Type: GrantFiled: August 31, 2021Date of Patent: January 16, 2024Assignee: eBay Inc.Inventors: Farah Abdallah, Robert Enyedi, Amit Srivastava, Elaine Lee, Braddock Craig Gaskill, Tomer Lancewicki, Xinyu Zhang, Jayanth Vasudevan, Dominique Jean Bouchon
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Publication number: 20210390365Abstract: Aspect pre-selection techniques using machine learning are described. In one example, an artificial assistant system is configured to implement a chat bot. A user then engages in a first natural-language conversation. As part of this first natural-language conversation, a communication is generated by the chat bot to prompt the user to specify an aspect of a category that is a subject of a first natural-language conversation and user data is received in response. Data that describes this first natural-language conversation is used to train a model using machine learning. Data, is then be received by the chat bot as part of a second natural-language conversation. This data, from the second natural-language conversation, is processed using the model as part of machine learning to generate the second search query to include the aspect of the category automatically and without user intervention.Type: ApplicationFiled: August 31, 2021Publication date: December 16, 2021Applicant: eBay Inc.Inventors: Farah Abdallah, Robert Enyedi, Amit Srivastava, Elaine Lee, Braddock Craig Gaskill, Tomer Lancewicki, Xinyu Zhang, Jayanth Vasudevan, Dominique Jean Bouchon
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Patent number: 11144811Abstract: Aspect pre-selection techniques using machine learning are described. In one example, an artificial assistant system is configured to implement a chat bot. A user then engages in a first natural-language conversation. As part of this first natural-language conversation, a communication is generated by the chat bot to prompt the user to specify an aspect of a category that is a subject of a first natural-language conversation and user data is received in response. Data that describes this first natural-language conversation is used to train a model using machine learning. Data, is then be received by the chat bot as part of a second natural-language conversation. This data, from the second natural-language conversation, is processed using the model as part of machine learning to generate the second search query to include the aspect of the category automatically and without user intervention.Type: GrantFiled: December 29, 2017Date of Patent: October 12, 2021Assignee: eBay Inc.Inventors: Farah Abdallah, Robert Enyedi, Amit Srivastava, Elaine Lee, Braddock Craig Gaskill, Tomer Lancewicki, Xinyu Zhang, Jayanth Vasudevan, Dominique Jean Bouchon
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Publication number: 20190156177Abstract: Aspect pre-selection techniques using machine learning are described. In one example, an artificial assistant system is configured to implement a chat bot. A user then engages in a first natural-language conversation. As part of this first natural-language conversation, a communication is generated by the chat bot to prompt the user to specify an aspect of a category that is a subject of a first natural-language conversation and user data is received in response. Data that describes this first natural-language conversation is used to train a model using machine learning. Data, is then be received by the chat bot as part of a second natural-language conversation. This data, from the second natural-language conversation, is processed using the model as part of machine learning to generate the second search query to include the aspect of the category automatically and without user intervention.Type: ApplicationFiled: December 29, 2017Publication date: May 23, 2019Applicant: eBay Inc.Inventors: Farah Abdallah, Robert Enyedi, Amit Srivastava, Elaine Lee, Braddock Craig Gaskill, Tomer Lancewicki, Xinyu Zhang, Jayanth Vasudevan, Dominique Jean Bouchon
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Patent number: 8121866Abstract: A method for simultaneously displaying a procedure documentation form and pediatric cardiology z-scores for a patient is provided. Documentation data for the patient is received and a database including pediatric cardiology data for a computerized z-score graph appropriate for a patient is accessed. The pediatric cardiology data and documentation data are utilized to calculate one or more z-scores for the patient. The one or more z-scores are displayed on a computerized graph simultaneously with the procedure documentation form.Type: GrantFiled: June 29, 2007Date of Patent: February 21, 2012Assignee: Cerner Innovation, Inc.Inventors: C. Cameron Brackett, Craig A. Gaskill, Michael Harkavy
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Publication number: 20080059243Abstract: A method for simultaneously displaying a procedure documentation form and pediatric cardiology z-scores for a patient is provided. Documentation data for the patient is received and a database including pediatric cardiology data for a computerized z-score graph appropriate for a patient is accessed. The pediatric cardiology data and documentation data are utilized to calculate one or more z-scores for the patient. The one or more z-scores are displayed on a computerized graph simultaneously with the procedure documentation form.Type: ApplicationFiled: June 29, 2007Publication date: March 6, 2008Applicant: CERNER INNOVATION, INC.Inventors: C. BRACKETT, CRAIG GASKILL, MICHAEL HARKAVY