Patents by Inventor Lee Evan Kohn
Lee Evan Kohn 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: 11748646Abstract: A system includes a processor and a memory device communicatively coupled to the processor. The system also includes a database communicatively coupled to the processor. The database is configured to store a first plurality of prediction sets. Each prediction set is associated with a respective individual within a first population. Each prediction set comprises a plurality of prediction results, and each prediction result corresponds to a selected one of a plurality of features. The processor is configured to receive a request for a distribution value associated with a selected feature and one or more parameters. The distribution value indicate how often the selected feature appears in a second population of individuals, the second population being defined by the one or more parameters.Type: GrantFiled: September 15, 2017Date of Patent: September 5, 2023Assignee: Zoomph, Inc.Inventors: Thomas Mathew, John William Seaman, Jorge Luis Vasquez, Reza Ali Manouchehri, Lee Evan Kohn
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Patent number: 11636367Abstract: One example method of operation may include identifying a number of features associated with information of one or more entities, accessing a probability distribution store comprising defined numerical ranges as potential possibilities for being paired with the features of the one or more entities, determining first probability distributions for each of the defined numerical ranges indicating probabilities that each defined numerical range is assigned to each entity having one or more of the features, determining second probability distributions for each of the defined numerical ranges indicating probabilities that each defined numerical range is assigned to each entity having one or more additional features, determining a merged probability distribution based on the first probability distributions and the second probability distributions, determining and storing one or more prediction sets based on the merged probability distribution, selecting one or more content items to display on a device interface basedType: GrantFiled: February 20, 2021Date of Patent: April 25, 2023Assignee: Zoomph, Inc.Inventors: Ali Reza Manouchehri, Jorge Luis Vasquez, Thomas Mathew, John William Seaman, Lee Evan Kohn
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Patent number: 11257000Abstract: An individual having a plurality of first features and a second characteristic is identified. A plurality of second features associated with a second characteristic is determined. For each first feature among the plurality of first features, a respective probability distribution indicating, for each respective second feature, a probability that a person having the respective second feature has the first feature, is determined, thereby generating a plurality of probability distributions. A probabilistic classifier is used to combine the plurality of probability distributions, thereby generating a merged probability distribution. A Monte Carlo method is used to generate a prediction set based on the merged probability distribution, the prediction set including a plurality of prediction values for the second characteristic of the individual, each respective prediction value being associated with one of the plurality of second features. The prediction set is stored in a memory.Type: GrantFiled: May 9, 2018Date of Patent: February 22, 2022Assignee: Zoomph, Inc.Inventors: Thomas Mathew, John William Seaman, Ali Reza Manouchehri, Jorge Luis Vasquez, Lee Evan Kohn
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Publication number: 20210174234Abstract: One example method of operation may include identifying a number of features associated with information of one or more entities, accessing a probability distribution store comprising defined numerical ranges as potential possibilities for being paired with the features of the one or more entities, determining first probability distributions for each of the defined numerical ranges indicating probabilities that each defined numerical range is assigned to each entity having one or more of the features, determining second probability distributions for each of the defined numerical ranges indicating probabilities that each defined numerical range is assigned to each entity having one or more additional features, determining a merged probability distribution based on the first probability distributions and the second probability distributions, determining and storing one or more prediction sets based on the merged probability distribution, selecting one or more content items to display on a device interface basedType: ApplicationFiled: February 20, 2021Publication date: June 10, 2021Applicant: Zoomph, Inc.Inventors: Thomas MATHEW, John William Seaman, Ali Reza MANOUCHEHRI, Jorge Luis VASQUEZ, Lee Evan KOHN, Thomas MATHEW, John William Seaman, Ali Reza MANOUCHEHRI, Jorge Luis VASQUEZ, Lee Evan KOHN
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Patent number: 10963806Abstract: An individual having a plurality of first features and a second characteristic is identified. A plurality of second features associated with a second characteristic is determined. For each first feature among the plurality of first features, a respective probability distribution indicating, for each respective second feature, a probability that a person having the respective second feature has the first feature, is determined, thereby generating a plurality of probability distributions. A probabilistic classifier is used to combine the plurality of probability distributions, thereby generating a merged probability distribution. A Monte Carlo method is used to generate a prediction set based on the merged probability distribution, the prediction set including a plurality of prediction values for the second characteristic of the individual, each respective prediction value being associated with one of the plurality of second features. The prediction set is stored in a memory.Type: GrantFiled: May 12, 2017Date of Patent: March 30, 2021Inventors: Thomas Mathew, John William Seaman, Ali Reza Manouchehri, Jorge Luis Vasquez, Lee Evan Kohn
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Publication number: 20180260728Abstract: An individual having a plurality of first features and a second characteristic is identified. A plurality of second features associated with a second characteristic is determined. For each first feature among the plurality of first features, a respective probability distribution indicating, for each respective second feature, a probability that a person having the respective second feature has the first feature, is determined, thereby generating a plurality of probability distributions. A probabilistic classifier is used to combine the plurality of probability distributions, thereby generating a merged probability distribution. A Monte Carlo method is used to generate a prediction set based on the merged probability distribution, the prediction set including a plurality of prediction values for the second characteristic of the individual, each respective prediction value being associated with one of the plurality of second features. The prediction set is stored in a memory.Type: ApplicationFiled: May 9, 2018Publication date: September 13, 2018Applicant: Zoomph, Inc.Inventors: Thomas MATHEW, John William Seaman, Ali Reza MANOUCHEHRI, Jorge Luis VASQUEZ, Lee Evan KOHN
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Patent number: 9996800Abstract: An individual having a plurality of first features and a second characteristic is identified. A plurality of second features associated with a second characteristic is determined. For each first feature among the plurality of first features, a respective probability distribution indicating, for each respective second feature, a probability that a person having the respective second feature has the first feature, is determined, thereby generating a plurality of probability distributions. A probabilistic classifier is used to combine the plurality of probability distributions, thereby generating a merged probability distribution. A Monte Carlo method is used to generate a prediction set based on the merged probability distribution, the prediction set including a plurality of prediction values for the second characteristic of the individual, each respective prediction value being associated with one of the plurality of second features. The prediction set is stored in a memory.Type: GrantFiled: November 9, 2016Date of Patent: June 12, 2018Assignee: Zoomph, Inc.Inventors: Thomas Mathew, John William Seaman, Ali Reza Manouchehri, Jorge Luis Vasquez, Lee Evan Kohn
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Publication number: 20180129962Abstract: A system includes a processor and a memory device communicatively coupled to the processor. The system also includes a database communicatively coupled to the processor. The database is configured to store a first plurality of prediction sets. Each prediction set is associated with a respective individual within a first population. Each prediction set comprises a plurality of prediction results, and each prediction result corresponds to a selected one of a plurality of features. The processor is configured to receive a request for a distribution value associated with a selected feature and one or more parameters. The distribution value indicate how often the selected feature appears in a second population of individuals, the second population being defined by the one or more parameters.Type: ApplicationFiled: September 15, 2017Publication date: May 10, 2018Applicant: Zoomph, Inc.Inventors: Thomas Mathew, John William Seaman, Jorge Luis Vasquez, Reza Ali Manouchehri, Lee Evan Kohn
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Publication number: 20170300826Abstract: An individual having a plurality of first features and a second characteristic is identified. A plurality of second features associated with a second characteristic is determined. For each first feature among the plurality of first features, a respective probability distribution indicating, for each respective second feature, a probability that a person having the respective second feature has the first feature, is determined, thereby generating a plurality of probability distributions. A probabilistic classifier is used to combine the plurality of probability distributions, thereby generating a merged probability distribution. A Monte Carlo method is used to generate a prediction set based on the merged probability distribution, the prediction set including a plurality of prediction values for the second characteristic of the individual, each respective prediction value being associated with one of the plurality of second features. The prediction set is stored in a memory.Type: ApplicationFiled: May 12, 2017Publication date: October 19, 2017Applicant: Zoomph, Inc.Inventors: Thomas MATHEW, John William Seaman, Ali Reza MANOUCHEHRI, Jorge Luis VASQUEZ, Lee Evan KOHN
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Publication number: 20170169337Abstract: An individual having a plurality of first features and a second characteristic is identified. A plurality of second features associated with a second characteristic is determined. For each first feature among the plurality of first features, a respective probability distribution indicating, for each respective second feature, a probability that a person having the respective second feature has the first feature, is determined, thereby generating a plurality of probability distributions. A probabilistic classifier is used to combine the plurality of probability distributions, thereby generating a merged probability distribution. A Monte Carlo method is used to generate a prediction set based on the merged probability distribution, the prediction set including a plurality of prediction values for the second characteristic of the individual, each respective prediction value being associated with one of the plurality of second features. The prediction set is stored in a memory.Type: ApplicationFiled: November 9, 2016Publication date: June 15, 2017Inventors: Thomas MATHEW, John William Seaman, Ali Reza MANOUCHEHRI, Jorge Luis VASQUEZ, Lee Evan KOHN
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Patent number: 9524469Abstract: An individual having a plurality of first features and a second characteristic is identified. A plurality of second features associated with a second characteristic is determined. For each first feature among the plurality of first features, a respective probability distribution indicating, for each respective second feature, a probability that a person having the respective second feature has the first feature, is determined, thereby generating a plurality of probability distributions. A probabilistic classifier is used to combine the plurality of probability distributions, thereby generating a merged probability distribution. A Monte Carlo method is used to generate a prediction set based on the merged probability distribution, the prediction set including a plurality of prediction values for the second characteristic of the individual, each respective prediction value being associated with one of the plurality of second features. The prediction set is stored in a memory.Type: GrantFiled: December 14, 2015Date of Patent: December 20, 2016Assignee: Metrostar Systems, Inc.Inventors: Thomas Mathew, John William Seaman, Ali Reza Manouchehri, Jorge Luis Vasquez, Lee Evan Kohn