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公开(公告)号：US10373511B2
公开(公告)日：2019-08-06
申请号：US15257843
申请日：2016-09-06
摘要： Techniques pertaining to automating generation of curricula for a class of students with blended-learning contents are presented. The blended-leaning contents provide common topics shared by all the students in a class as well as self-learning materials for sub-groups of the class. This approach creates curricula optimally attending to students with different interests and backgrounds. The course materials are selected by searching multiple external sources publically available while filtering the search results through inputs of the students and requirements set by the instructors. The course contents and schedules of the curricula are further optimized by organizing the filtered search results with respect to a set of constraints.
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公开(公告)号：US20170364803A1
公开(公告)日：2017-12-21
申请号：US15236215
申请日：2016-08-12
发明人： Flavio D. Calmon , Fenno F. Heath, III , Richard B. Hull , Elham Khabiri , Matthew D. Riemer , Aditya Vempaty
CPC分类号： G06N3/0454 , G06Q30/0201
摘要： A method and system are provided to calculate a future behavioral data and identify a relative causal impact of external factors affecting the data. Behavioral data and data for one or more external factors are harvested for a first time period. New behavioral data is harvested for a second time period. New data for the second time period is harvested. Based on a second training algorithm, a forecast time series value of a future behavioral data for a third time period that is after the second time period is calculated. A relative causal impact between each external factor and the predicted time series value of the behavioral data, for the third time period, is identified.
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公开(公告)号：US11106995B2
公开(公告)日：2021-08-31
申请号：US15440303
申请日：2017-02-23
IPC分类号： G06N20/00 , G06F17/18 , H04L29/08 , G06F17/11 , G06F16/28 , G06F16/901 , G06Q50/00 , G06Q30/02
摘要： A method for generating an output comprising one or more segments includes obtaining a plurality of profiles derived from unstructured data associated with a plurality of users, wherein a given one of the profiles corresponds to a respective one of the users; repetitively executing at least one machine learning technique on the plurality of profiles, each execution producing a respective set of one or more segments from the plurality of profiles; generating a complete graph by performing pairwise comparisons between sets of segments from respective executions; applying at least one persistency graph algorithm to the complete graph to find one or more coherent clusters comprising one or more segments that are persistent across the repetitive executions of the machine learning technique; and producing the output at least in part by selecting at least one of the segments from at least one of the coherent clusters.
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公开(公告)号：US20200227035A1
公开(公告)日：2020-07-16
申请号：US16244905
申请日：2019-01-10
摘要： A system, apparatus and a method for determining distinguishable data, includes processing input data into a plurality of elements, calculating distinguishability of the plurality of elements using phonetic vowels, and determining distinguishable elements from among the plurality of elements, according to the distinguishability calculation.
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公开(公告)号：US20190130776A1
公开(公告)日：2019-05-02
申请号：US15796044
申请日：2017-10-27
发明人： Srirupa Chakraborty , Payel Das , Aditya Vempaty
摘要： Embodiments relate to a system, program product, and method for use with an intelligent (AI) computer platform to explore real-world modeling. A sensory input data signal is communicated to the AI platform and translated into a corresponding scenario. The translation is directed at an associated force and application of the force to a selected or identified object and environment. A reaction to the application is created, and reaction data is converted to a sensory output signal. Receipt of the sensory output signal by a corresponding sensory output device creates a physical manifestation of generated feedback of the reaction data to a sensory medium. The embodiments are directed at both learning and assessment, and leverage a corpus with the AI platform in support of an interactive learning experience.
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公开(公告)号：US20190130284A1
公开(公告)日：2019-05-02
申请号：US15796099
申请日：2017-10-27
发明人： Srirupa Chakraborty , Payel Das , Aditya Vempaty
摘要： Sensory input data signal is communicated to an AI platform and translated into a corresponding scenario. The translation is directed at an associated force and application of the force to a selected or identified object and environment. Real-time analysis of the force is applied, which includes modeling an expected behavior. An assessment response is received and compared to a corpus. A solution in the corpus proximal to the assessment response is identified, and a reaction of proximity of the response to the identified solution is created. Proximity data is converted to a sensory output signal. Receipt of the sensory output signal by a corresponding sensory output device creates a physical manifestation of generated feedback of the reaction data to a sensory medium. Embodiments are directed at both learning and assessment, and leverage a corpus with the AI platform in support of an interactive learning experience.
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公开(公告)号：US11106999B2
公开(公告)日：2021-08-31
申请号：US15859554
申请日：2017-12-31
IPC分类号： G06N20/00 , G06F17/18 , H04L29/08 , G06F17/11 , G06F16/28 , G06F16/901 , G06Q50/00 , G06Q30/02
摘要： A method for generating an output comprising one or more segments includes obtaining a plurality of profiles derived from unstructured data associated with a plurality of users, wherein a given one of the profiles corresponds to a respective one of the users; repetitively executing at least one machine learning technique on the plurality of profiles, each execution producing a respective set of one or more segments from the plurality of profiles; generating a complete graph by performing pairwise comparisons between sets of segments from respective executions; applying at least one persistency graph algorithm to the complete graph to find one or more coherent clusters comprising one or more segments that are persistent across the repetitive executions of the machine learning technique; and producing the output at least in part by selecting at least one of the segments from at least one of the coherent clusters.
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公开(公告)号：US11062616B2
公开(公告)日：2021-07-13
申请号：US15796044
申请日：2017-10-27
发明人： Srirupa Chakraborty , Payel Das , Aditya Vempaty
摘要： Embodiments relate to a system, program product, and method for use with an intelligent (AI) computer platform to explore real-world modeling. A sensory input data signal is communicated to the AI platform and translated into a corresponding scenario. The translation is directed at an associated force and application of the force to a selected or identified object and environment. A reaction to the application is created, and reaction data is converted to a sensory output signal. Receipt of the sensory output signal by a corresponding sensory output device creates a physical manifestation of generated feedback of the reaction data to a sensory medium. The embodiments are directed at both learning and assessment, and leverage a corpus with the AI platform in support of an interactive learning experience.
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公开(公告)号：US20210117794A1
公开(公告)日：2021-04-22
申请号：US17135384
申请日：2020-12-28
发明人： Swapna Buccapatnam Tirumala , Ashish Jagmohan , Elham Khabiri , Ta-Hsin Li , Matthew Daniel Riemer , Vadim Sheinin , Aditya Vempaty
IPC分类号： G06N3/08 , G06K9/00 , G06N20/00 , G06F16/33 , G06K9/62 , G06N3/04 , G06F40/30 , G06F40/242 , G06F40/295
摘要： Techniques for mapping policy documents to regulatory documents to check for compliance between the policies and documents are provided. In one example, a computer-implemented method determining, by a system operatively coupled to a processor, an information input, a control framework, and a document from a first group consisting of a regulatory document and a policy document, wherein the information input is a corpora from a second group consisting of a domain corpora and a global corpora. The computer-implemented method can also comprise mapping, by the system, the received regulatory document or the received policy document to the control framework using a supervised machine learning technique.
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公开(公告)号：US20180240042A1
公开(公告)日：2018-08-23
申请号：US15859554
申请日：2017-12-31
CPC分类号： G06N20/00 , G06F16/285 , G06F16/9024 , G06F17/11 , G06F17/18 , G06Q30/02 , G06Q50/01 , H04L67/306
摘要： A method for generating an output comprising one or more segments includes obtaining a plurality of profiles derived from unstructured data associated with a plurality of users, wherein a given one of the profiles corresponds to a respective one of the users; repetitively executing at least one machine learning technique on the plurality of profiles, each execution producing a respective set of one or more segments from the plurality of profiles; generating a complete graph by performing pairwise comparisons between sets of segments from respective executions; applying at least one persistency graph algorithm to the complete graph to find one or more coherent clusters comprising one or more segments that are persistent across the repetitive executions of the machine learning technique; and producing the output at least in part by selecting at least one of the segments from at least one of the coherent clusters.
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