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公开(公告)号：US20220164606A1
公开(公告)日：2022-05-26
申请号：US16953587
申请日：2020-11-20
发明人： Ravi Chandra Chamarthy , Manish Anand Bhide , Madhavi Katari , Arunkumar Kalpathi Suryanarayanan
摘要： A machine learning model data quality improvement detection tool is provided for identifying an accurate reference group and an accurate monitored group of a machine learning model. The tool monitors a behavior of the machine learning model for a predetermined time frame. The tool compares a determined fairness metric a pre-defined fairness threshold. Responsive to the fairness metric failing to meet the pre-defined fairness threshold, the tool modifies the monitored group to include a first portion of the reference group. The tool compares a newly determined fairness metric to the pre-defined fairness threshold. Responsive to the newly determined fairness metric meeting the pre-defined fairness threshold, the tool identifies the modified monitored group including the first portion of the user-defined reference group as a new monitored group and the modified reference group without the first portion of the user-defined reference group as a new reference group.
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12.发明申请公开(公告)号：US20220164434A1
公开(公告)日：2022-05-26
申请号：US17100235
申请日：2020-11-20
发明人： Sri Harsha Varada , Sunita Rani Nayak , Hari Krishna Prasad Bheemavarapu , Karthik Adatrow , Manish Anand Bhide
摘要： Aspects of the present invention disclose a method for dynamic password inducing techniques for security configuration and validation of a user. The method includes one or more processors identifying textual data of a user. The method further includes generating a set of password parameters for a password. The method further includes identifying one or more password dynamisms of the user from one or more sources, where the one or more password dynamisms are dynamic inputs, from the user, to an authentication device. The method further includes modifying the textual data to include a text placeholder, wherein the text placeholder includes a replacement parameter that induces the user to provide a password dynamism. The method further includes configuring the set of password parameters for the password of the user based at least in part on the one or more password dynamisms of the user from the one or more sources.
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公开(公告)号：US20220083899A1
公开(公告)日：2022-03-17
申请号：US17018477
申请日：2020-09-11
IPC分类号： G06N20/00
摘要： A processor may receive an original dataset. The processor may segment, automatically, the original dataset into a plurality of data groups. The plurality of data groups may include a model training dataset and a holdout dataset. The processor may generate a model with the model training dataset. The processor may validate the model with the holdout dataset.
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公开(公告)号：US11205138B2
公开(公告)日：2021-12-21
申请号：US16419116
申请日：2019-05-22
发明人： Samiulla Zakir Hussain Shaikh , Himanshu Gupta , Rajmohan Chandrahasan , Sameep Mehta , Manish Anand Bhide
IPC分类号： G06N20/00
摘要： A method, computer system, and a computer program product for utilizing provenance data to improve machine learning is provided. Embodiments of the present invention may include collecting provenance data. Embodiments of the present invention may include identifying model quality improvements based on the collected provenance data. Embodiments of the present invention may include identifying related models based on the collected provenance data. Embodiments of the present invention may include recommending model quality improvements to a user.
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公开(公告)号：US11204953B2
公开(公告)日：2021-12-21
申请号：US16853414
申请日：2020-04-20
IPC分类号： G06F7/00 , G06F16/335 , G06F16/36 , G06Q10/06 , G06F16/38 , G06F16/332
摘要： One embodiment provides a method, including: generating a plurality of ontologies wherein each ontology is generated by: monitoring interactions of a user with lineage information, wherein the monitoring comprises monitoring (i) filter interactions and (ii) access interactions; aggregating the monitored interactions of the user with monitored interactions of other users having a given business role; and generating an ontology for the given business role, wherein the subset comprises (i) event types, (ii) event constraints, (iii) event metadata, and (iv) event context; and upon a user having one of the plurality of business roles accessing lineage information on the data platform, providing a subset of the lineage information.
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公开(公告)号：US11106864B2
公开(公告)日：2021-08-31
申请号：US16361385
申请日：2019-03-22
发明人： Manish Anand Bhide , Nishtha Madaan , Seema Nagar , Sameep Mehta , Kuntal Dey
IPC分类号： G06F40/00 , G06F40/169 , G06F16/2457 , G06F40/117 , G06F40/197
摘要： An article is automatically augmented. The article and one or more comments are received. Comment elements are extracted from the one or more comments, and article elements are extracted from the article. Alignment scores are generated for comment-article pairs based on the extracted comment and article elements. Further, it is determined that at least one comment-article pair has an alignment score at or above a threshold alignment score. At least one augmentation feature is then generated.
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公开(公告)号：US11086754B2
公开(公告)日：2021-08-10
申请号：US16460182
申请日：2019-07-02
摘要： Approaches presented herein enable optimization of a developing application to a user base. More specifically, application-centric data is gathered during a cultivation phase of the developing application. Substantially concurrently with the cultivation phase of the developing application, the application-centric data is analyzed according to static code of the developing application, a testing of the developing application, or a user experience (UX) design of the developing application. A machine learning model is applied to the analyzed application-centric data. This machine learning model is trained on historic application feedback data from applications available to the user base. Based on the machine learning model, a recommended change to optimize the developing application to the user base is generated.
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公开(公告)号：US20210209540A1
公开(公告)日：2021-07-08
申请号：US16733429
申请日：2020-01-03
摘要： Managing notifications is provided. Personal monitoring system inputs corresponding to each member of a defined group performing a common task are contextually analyzed to identify a notification sequence for each respective member enabling task performance in a synchronized manner. Progress of each respective member while performing activities corresponding to the common task is analyzed using the personal monitoring system inputs to enable dynamic modification of the notification sequence and content to the members in accordance with the progress. Existence of any problem is identified during performance of activities corresponding to the common task to accordingly modify the notification sequence and content to target members for mitigation of an existing problem. Alignment of one or more members with a completion timeline for a given activity corresponding to the common task is identified for automatic notification suppression of a planned notification upon completion of the given activity within the completion timeline.
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公开(公告)号：US20240111995A1
公开(公告)日：2024-04-04
申请号：US17937876
申请日：2022-10-04
发明人： Manish Anand Bhide , Prateek Goyal
CPC分类号： G06N3/0454 , G06N3/088
摘要： One or more systems, devices, computer program products and/or computer-implemented methods of use provided herein relate to predicting bias in an artificial intelligence (AI) model. A system can comprise a memory configured to store computer executable components; and a processor configured to execute the computer executable components stored in the memory, wherein the computer executable components can comprise a data generation component that can generate a set of structured test data to test likelihood of an AI model generating biased outputs, based on analysis of payload logging data; and an alerting component that can alert a user of likelihood that the AI model will generate the biased outputs, wherein the alerting component can generate an alert in response to at least a first set of records approaching a defined threshold.
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公开(公告)号：US20230393848A1
公开(公告)日：2023-12-07
申请号：US17805233
申请日：2022-06-03
IPC分类号： G06F9/54
CPC分类号： G06F9/544
摘要： Early indications of application programming interface (API) usage are identified by correlation to particular issues with the API including singular and mutual consistency, completeness, accuracy, and staleness. Analysis of API input and output along with data type and formatting information facilitates identification of the API issues. Establishing a correlation between API usage and issues supports early detection of potential usage reduction on a case-by-case level. Corrective action to resolve identified issues may be performed in a timely manner to maintain usage levels.
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