Patents by Inventor Abdelhalim Abbas
Abdelhalim Abbas 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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Patent number: 12205725Abstract: The methods and apparatus disclosed herein can evaluate a subject for a developmental condition or conditions and provide improved sensitivity and specificity for categorical determinations indicating the presence or absence of the developmental condition by isolating hard-to-screen cases as inconclusive. The methods and apparatus disclosed herein can be configured to be tunable to control the tradeoff between coverage and reliability and to adapt to different application settings and can further be specialized to handle different population groups.Type: GrantFiled: February 2, 2022Date of Patent: January 21, 2025Assignee: Cognoa, Inc.Inventors: Brent Vaughan, Clara Lajonchere, Dennis Wall, Abdelhalim Abbas, Jeffrey Ford Garberson
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Patent number: 11972336Abstract: Disclosed herein is a machine learning platform and system for data analysis including for purposes of providing digital evaluations and therapeutics.Type: GrantFiled: March 9, 2022Date of Patent: April 30, 2024Assignee: Cognoa, Inc.Inventors: Brent Vaughan, Abdelhalim Abbas, Dennis Wall
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Patent number: 11862339Abstract: Disclosed herein are platforms, systems, devices, methods and media for model optimization and data analysis using machine learning. Input data can be processed and analyzed to identify relevant discriminating features, which can be modeled using a plurality of machine learning models. A computing device can be configured with one or more optimized models for categorizing input data.Type: GrantFiled: November 1, 2021Date of Patent: January 2, 2024Assignee: COGNOA, INC.Inventors: Dennis Wall, Sharief Khalil Taraman, Brent Vaughan, Abdelhalim Abbas
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Patent number: 11176444Abstract: Disclosed herein are platforms, systems, devices, methods and media for model optimization and data analysis using machine learning. Input data can be processed and analyzed to identify relevant discriminating features, which can be modeled using a plurality of machine learning models. A computing device can be configured with one or more optimized models for categorizing input data.Type: GrantFiled: November 3, 2020Date of Patent: November 16, 2021Assignee: COGNOA, INC.Inventors: Dennis Wall, Sharief Khalil Taraman, Brent Vaughan, Abdelhalim Abbas
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Patent number: 10409821Abstract: Various embodiments include systems and methods for search result ranking using machine learning. A goal model can be created using machine learning. Responsive to a search query, a plurality of data factors can be inputted into the goal model to create a model output. Search results can be presented to a user based on the model output.Type: GrantFiled: September 30, 2014Date of Patent: September 10, 2019Assignee: eBay, Inc.Inventors: Parashuram Kulkarni, Abdelhalim Abbas, Michael Mathieson, Jingzhou Hua, Jon Degenhardt, Ramakrishnan Natarajan
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Patent number: 10229190Abstract: An application classifier classifies applications using latent semantic indexing (LSI) vectors of the applications. The application classifier uses a machine-learned model generated based on pairs of LSI vectors of positive and negative training sets of applications, where the positive training set includes applications within a desired category and the negative training set includes applications outside of the desired category. For a given application, the application classifier determines whether the application belongs to the desired category based on similarity of an LSI vector of the application and LSI vectors of positive and negative exemplar applications, as determined by the machine-learned model. If the LSI vector of the application is similar to an LSI vector of at least one positive exemplar application and not similar to an LSI vector of any of the negative exemplar applications, the application is determined to belong to the desired category.Type: GrantFiled: May 7, 2014Date of Patent: March 12, 2019Assignee: Samsung Electronics Co., Ltd.Inventors: Abdelhalim Abbas, Eric Glover, Kyle D. Ross
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Publication number: 20190019581Abstract: The methods and apparatus disclosed herein provide digital diagnostics and digital therapeutics to patients. The digital personalized medicine system uses digital data to assess or diagnose symptoms of a patient, and feedback from the patient response to treatment is considered to update the personalized therapeutic interventions. The methods and apparatus disclosed herein can also diagnose and treat cognitive function of a subject, with fewer questions, decreased amounts of time, and determine a plurality of behavioral, neurological or mental health disorders, and provide clinically acceptable sensitivity and specificity in the diagnosis and treatment.Type: ApplicationFiled: June 15, 2018Publication date: January 17, 2019Inventors: Brent Vaughan, Abdelhalim Abbas
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Patent number: 9741039Abstract: A system and method of click modeling are disclosed. A ranking algorithm is modified using a click model. The click model makes inferences based on user click data. The user click data includes indications of user intent to transact a shopping action for an item for sale. Item listings are ranked for a search results page using the ranking algorithm in response to receiving a search query. Each item listing comprises an item for sale on an e-commerce site. The user click data can also include user clicks of item listings in a search results page. The shopping action can include bidding on an item for sale or purchasing an item for sale.Type: GrantFiled: November 19, 2012Date of Patent: August 22, 2017Assignee: eBay Inc.Inventor: Abdelhalim Abbas
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Publication number: 20150186495Abstract: An application classifier classifies applications using latent semantic indexing (LSI) vectors of the applications. The application classifier uses a machine-learned model generated based on pairs of LSI vectors of positive and negative training sets of applications, where the positive training set includes applications within a desired category and the negative training set includes applications outside of the desired category. For a given application, the application classifier determines whether the application belongs to the desired category based on similarity of an LSI vector of the application and LSI vectors of positive and negative exemplar applications, as determined by the machine-learned model. If the LSI vector of the application is similar to an LSI vector of at least one positive exemplar application and not similar to an LSI vector of any of the negative exemplar applications, the application is determined to belong to the desired category.Type: ApplicationFiled: May 7, 2014Publication date: July 2, 2015Applicant: Quixey, Inc.Inventors: Abdelhalim Abbas, Eric Glover, Kyle D. Ross
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Publication number: 20150186974Abstract: A method includes performing a search of an application data store using a search query. The application data store includes application data for a plurality of software applications available from a software-application marketplace. The application data includes a set of application statistics for each software application. Each set of application statistics includes statistical data points over time. The application data also includes a set of market-wide statistics that is an aggregate of the sets of application statistics over time. The method further includes generating a list of software applications identified during the search. Additionally, the method includes generating a result score for each software application in the list based on a set of market-adjusted statistics associated with the software application.Type: ApplicationFiled: December 30, 2013Publication date: July 2, 2015Inventors: Abdelhalim Abbas, Eric Glover
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Publication number: 20150088489Abstract: Systems and methods are disclosed for performing man-machine interaction with a user by capturing audible signals and video signals from an environment; detecting a communication context from the audio and video signals; looking up the context in an etiquette database; communicating without disrupting the user and if not possible, determining an appropriate time and fashion to interrupt the user; and communicating with the user at the appropriate time in the appropriate fashion.Type: ApplicationFiled: September 20, 2013Publication date: March 26, 2015Inventor: Abdelhalim Abbas
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Publication number: 20150058331Abstract: Various embodiments include systems and methods for search result ranking using machine learning. A goal model can be created using machine learning. Responsive to a search query, a plurality of data factors can be inputted into the goal model to create a model output. Search results can be presented to a user based on the model output.Type: ApplicationFiled: September 30, 2014Publication date: February 26, 2015Inventors: Parashuram Kulkarni, Abdelhalim Abbas, Michael Mathieson, Jingzhou Hua, Jon Degenhardt, Ramakrishnan Natarajan
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Patent number: 8924314Abstract: Various embodiments include systems and methods for search result ranking using machine learning. A goal model can be created using machine learning. Responsive to a search query, a plurality of data factors can be inputted into the goal model to create a model output. Search results can be presented to a user based on the model output.Type: GrantFiled: August 4, 2011Date of Patent: December 30, 2014Assignee: eBay Inc.Inventors: Parashuram Kulkarni, Abdelhalim Abbas, Michael Mathieson, Jingzhou Hua, Jon Degenhardt, Ramakrishnan Natarajan
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Publication number: 20140280098Abstract: An application search system compensates for game bias in search results using a gaminess value representing the likelihood that an application is a game. The application search system receives a gaminess value for an application from an external source, such as an operator, or automatically determines the gaminess value using a trained computer model. The computer model may be trained based on a supervised training set of data. The gaminess value of an application is used to determine relevance of applications responsive to a search query. In one configuration, the gaminess value is incorporated as a scoring feature by the application search system in a computer-learned relevance search. The gaminess value may be used as a relevance factor even when the search does not indicate a user's desire to search for a game.Type: ApplicationFiled: March 17, 2014Publication date: September 18, 2014Applicant: Quixey, Inc.Inventors: Eric Glover, Abdelhalim Abbas
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Publication number: 20130132226Abstract: A system and method of click modeling are disclosed. A ranking algorithm is modified using a click model. The click model makes inferences based on user click data. The user click data includes indications of user intent to transact a shopping action for an item for sale. Item listings are ranked for a search results page using the ranking algorithm in response to receiving a search query. Each item listing comprises an item for sale on an e-commerce site. The user click data can also include user clicks of item listings in a search results page. The shopping action can include bidding on an item for sale or purchasing an item for sale.Type: ApplicationFiled: November 19, 2012Publication date: May 23, 2013Applicant: eBay Inc.Inventor: Abdelhalim Abbas
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Publication number: 20120197758Abstract: A method and a system generate a reputation value for a user in a network-based community. A processor-implemented transaction data collector module collects transaction data of users of a network-based community. A processor-implemented transaction graph generator module generates a transaction graph based on the collected transaction data. The transaction graph has a transaction relationship between two users, and a weight corresponding to the transaction relationship. The weight is representative of a mutually reinforcing relationship between two users. A processor-implemented reputation generator module generates a reputation value for a user from the transaction graph.Type: ApplicationFiled: January 27, 2011Publication date: August 2, 2012Applicant: eBay Inc.Inventors: Qian Zhong, Ramakrishnan Natarajan, Parashuram Kulkarni, Abdelhalim Abbas, Zhigang Hua
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Publication number: 20120078825Abstract: Various embodiments include systems and methods for search result ranking using machine learning. A goal model can be created using machine learning. Responsive to a search query, a plurality of data factors can be inputted into the goal model to create a model output. Search results can be presented to a user based on the model output.Type: ApplicationFiled: August 4, 2011Publication date: March 29, 2012Applicant: eBay Inc.Inventors: Parashuram Kulkarni, Abdelhalim Abbas, Michael Mathieson, Jingzhou Hua, Jon Degenhardt, Ramakrishnan Natarajan