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公开(公告)号：US20240330672A1
公开(公告)日：2024-10-03
申请号：US18129368
申请日：2023-03-31
发明人： Bhavya . , Yu Deng , Md Faisal Mahbub Chowdhury , Paulina Toro Isaza , Michael Elton Nidd , Amar Prakash Azad , Harshit Kumar , Larisa Shwartz
摘要： A method, system, and computer program product that is configured to: train at least one model based on a corpus of historical data comprising annotated historical tickets; extract a textual sequence of a historical ticket based on the at least one trained model; determine a sentiment of the textual sequence of the historical ticket; and generate mitigation guidance to mitigate an issue in a current ticket based on the textual sequence of the historical ticket and the determined sentiment of the textual sequence of the historical ticket.
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公开(公告)号：US20230004761A1
公开(公告)日：2023-01-05
申请号：US17363087
申请日：2021-06-30
发明人： Raghav Batta , Michael Elton Nidd , Larisa Shwartz , PRITAM GUNDECHA , Rama Kalyani T. Akkiraju , Amar Prakash Azad , Harshit Kumar
摘要： An approach for generating actionable explanations of change request classifications may be presented. A model may generate features associated with a change request may be disclosed. The model may be trained with historical change requests that have been labeled risky or not risky. The change request may be classified as risky or not risky. Candidate historical change requests with the same classification as the change request and occupying similar feature space as the change request may be identified from a historical change request repository. One or more features which had the most significant impact on the classification may be identified. A candidate historical change request with at least one significant feature impacting classification may be identified.
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公开(公告)号：US11409593B1
公开(公告)日：2022-08-09
申请号：US17394667
申请日：2021-08-05
发明人： Harshit Kumar , Raghav Batta , Jinho Hwang , Larisa Shwartz , Gargi B. Dasgupta , Prateeti Mohapatra , Amar Prakash Azad , Nikhil Verma , Ajay Gupta , Pooja Aggarwal , Jakub Krchák
IPC分类号： G06F11/07
摘要： Methods, computer program products, and/or systems are provided that perform the following operations: in an information technology (IT) management system, grouping one or more ongoing service failure events into a service failure record; identifying a representative event for the service failure record; identifying one or more conversations that relate to the one or more ongoing service events; computing, using a similarity algorithm, feature similarity scores for respective conversations of the one or more conversations based, at least in part, on the features associated with the representative event and features associated with the respective conversations; linking a subset of the one or more conversations to the one or more ongoing service events in the service failure record based, at least in part, on the computed feature similarity scores; and providing the service failure record to a collaboration platform utilized in addressing the one or more ongoing service events.
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公开(公告)号：US10921028B2
公开(公告)日：2021-02-16
申请号：US15891913
申请日：2018-02-08
发明人： Kalyan Kanti Dasgupta , Manikandan Padmanaban , Jagabondhu Hazra , Amar Prakash Azad , Shivkumar Kalyanaraman
IPC分类号： H01L31/042 , H02N6/00 , F24S50/20 , H01L31/054 , H02S50/00 , G05F1/67
摘要： One embodiment provides a method, including: receiving configuration input for a solar structure; the configuration input comprising (i) a geographical location, (ii) module configuration input, and (iii) reflector configuration input; identifying the position of the sun; determining an angle between the solar reflector and the solar module corresponding to a predetermined power gain for the solar module, wherein the determining comprises (i) identifying the corresponding area of the solar module that is illuminated by the solar reflector and (ii) totaling the contributions from each of the solar reflectors to calculate an irradiance for each solar cell; adjusting the angles of at least some of the solar reflectors with respect to the solar module to angles determined to correspond to the predetermined power gain using at least one actuator; and dynamically changing how the solar cells are electrically connected together to form a plurality of strings.
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5.发明公开公开(公告)号：US20230409832A1
公开(公告)日：2023-12-21
申请号：US17807160
申请日：2022-06-16
IPC分类号： G06F40/284 , G06F40/205 , G06F40/30 , G06F16/35 , G06N3/04
CPC分类号： G06F40/284 , G06F40/205 , G06F40/30 , G06F16/35 , G06N3/04
摘要： A method, computer program product and system are provided to generate perturbed text is provided. A processor receives a string of text from a user. A processor determines one or more classifications for at least one word in the string of text by a classification model. A processor determines a plurality of perturbations of the at least one word based on the one or more classifications, where the plurality of perturbations do not share the same one or more classifications as the least one word in the string of text. A processor selects a perturbation of the string of text based on (i) an edit distance between the string of text and the plurality of perturbations, and (ii) a fluency metric for each of the plurality of perturbations. A processor provides the perturbation of the string of text to the user.
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公开(公告)号：US20190242621A1
公开(公告)日：2019-08-08
申请号：US15891913
申请日：2018-02-08
发明人： Kalyan Kanti Dasgupta , Manikandan Padmanaban , Jagabondhu Hazra , Amar Prakash Azad , Shivkumar Kalyanaraman
IPC分类号： F24S50/20 , H01L31/054
CPC分类号： F24S50/20 , F24S2050/25 , H01L31/0547
摘要： One embodiment provides a method, including: receiving configuration input for a solar structure; the configuration input comprising (i) a geographical location, (ii) module configuration input, and (iii) reflector configuration input; identifying the position of the sun; determining an angle between the solar reflector and the solar module corresponding to a predetermined power gain for the solar module, wherein the determining comprises (i) identifying the corresponding area of the solar module that is illuminated by the solar reflector and (ii) totaling the contributions from each of the solar reflectors to calculate an irradiance for each solar cell; adjusting the angles of at least some of the solar reflectors with respect to the solar module to angles determined to correspond to the predetermined power gain using at least one actuator; and dynamically changing how the solar cells are electrically connected together to form a plurality of strings.
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公开(公告)号：US20230153225A1
公开(公告)日：2023-05-18
申请号：US17455035
申请日：2021-11-16
发明人： Amar Prakash Azad , Harshit Kumar , Raghav Batta , Michael Elton Nidd , Larisa Shwartz , PRITAM GUNDECHA , Alberto Giammaria
CPC分类号： G06F11/3604 , G06F8/70
摘要： In an approach to risk prediction for bug-introducing changes, a computer retrieves one or more historic pull requests. A computer determines a unique file linking for each file included in the historic pull requests. A computer generates a file risk dataset. A computer performs chronological partitioning on the file risk dataset. A computer determines bug-introducing changes in the file risk dataset. A computer computes a collaborative file association between two or more of the files in the file risk dataset. A computer labels each of the files in the file risk dataset with an associated risk of introducing a bug. A computer generates a labelled file risk inducing ground truth dataset. A computer inputs the labelled file risk inducing ground truth dataset to a file risk prediction model. A computer extracts pull request features from the historic pull requests. A computer generates a pull request risk prediction model.
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公开(公告)号：US11645188B1
公开(公告)日：2023-05-09
申请号：US17455035
申请日：2021-11-16
发明人： Amar Prakash Azad , Harshit Kumar , Raghav Batta , Michael Elton Nidd , Larisa Shwartz , Pritam Gundecha , Alberto Giammaria
CPC分类号： G06F11/3604 , G06F8/70 , G06F11/3608
摘要： In an approach to risk prediction for bug-introducing changes, a computer retrieves one or more historic pull requests. A computer determines a unique file linking for each file included in the historic pull requests. A computer generates a file risk dataset. A computer performs chronological partitioning on the file risk dataset. A computer determines bug-introducing changes in the file risk dataset. A computer computes a collaborative file association between two or more of the files in the file risk dataset. A computer labels each of the files in the file risk dataset with an associated risk of introducing a bug. A computer generates a labelled file risk inducing ground truth dataset. A computer inputs the labelled file risk inducing ground truth dataset to a file risk prediction model. A computer extracts pull request features from the historic pull requests. A computer generates a pull request risk prediction model.
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