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公开(公告)号：US12099628B2
公开(公告)日：2024-09-24
申请号：US17661780
申请日：2022-05-03
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： Jin Wang , Lei Gao , A Peng Zhang , Kai Li , Jun Wang , Xiao Ming Ma , Xin Feng Zhu , Geng Wu Yang
CPC classification number: G06F21/6245 , G06F16/35 , G06F18/23
Abstract: The present disclosure relates to privacy protection in a search process. According to a method, a target emotion vector is extracted from a search interaction, the target emotion vector representing emotional information in the search interaction. Respective emotion distances between the target emotion vector and respective emotion vectors associated with a plurality of text clusters are determined. The plurality of text clusters is clustered from a dictionary of text elements. A first number of text clusters are selected from the plurality of text clusters based on the determined respective emotion distances. The first number of text clusters have emotion distances larger than at least one unselected text cluster among the plurality of text clusters. A plurality of confused search interactions are constructed for the search interaction based on the first number of text clusters, and the plurality of confused search interactions are performed.
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公开(公告)号：US20230119654A1
公开(公告)日：2023-04-20
申请号：US17451495
申请日：2021-10-20
Applicant: International Business Machines Corporation
Inventor： Jin Wang , Lei Gao , Kai Li , A Peng Zhang , Yan Liu , Jia Xing Tang , Xin Feng Zhu
IPC: G06N20/00
Abstract: Identifying node importance in a machine learning pipeline is provided. Changes in accuracy of the machine learning pipeline are recorded for each respective node setting change in a randomly generated group of node settings inputted into each corresponding node included in the machine learning pipeline. A regression model is generated to determine a relationship between each respective node setting change in the randomly generated group of node settings inputted into each corresponding node and the changes in the accuracy of the machine learning pipeline. A node of importance is identified in the machine learning pipeline using the regression model based on the relationship between each respective node setting change in the randomly generated group of node settings inputted into each corresponding node and the changes in the accuracy of the machine learning pipeline.
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公开(公告)号：US20230119568A1
公开(公告)日：2023-04-20
申请号：US17504662
申请日：2021-10-19
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： Jin Wang , Lei Gao , A PENG ZHANG , Kai Li , Yan Liu
Abstract: A computer-implemented method includes: obtaining, by a computing device, data from sensors that collect the data in a system during a time, wherein the data is multi-dimensional time series data; creating, by the computing device, matrices based on the data; determining, by the computing device using a first computer-based numerical modeling method, patterns based on the matrices; creating, by the computing device using a second computer-based numerical modeling method, a single time series model based on the patterns; and predicting, by the computing device, a future condition of the system using the time series model with current data of the system.
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公开(公告)号：US11288173B1
公开(公告)日：2022-03-29
申请号：US17027780
申请日：2020-09-22
Applicant: International Business Machines Corporation
Inventor： Jin Wang , Lei Gao , A Peng Zhang , Si Er Han , Jing James Xu , Kai Li
Abstract: Test case selection methods are disclosed. A feature of a candidate test case and respective features of a set of test cases are extracted. The set of test cases is clustered into a plurality of clusters based on the respective features of the set of test cases. At least one cluster related to the candidate test case is determined from the plurality of clusters based on the feature of the candidate test case. At least one test case similar to the candidate test case is selected from a plurality of test cases included in the at least one cluster.
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公开(公告)号：US20240184567A1
公开(公告)日：2024-06-06
申请号：US18060794
申请日：2022-12-01
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： Lei Gao , Jin Wang , A PENG ZHANG , Kai Li , Matthew Wayne Howard
IPC: G06F8/71
CPC classification number: G06F8/71
Abstract: An embodiment for an improved method of automated version management for machine learning pipeline development is provided. The embodiment may compute a quality value of a target machine learning pipeline at a predetermined regular interval and automatically save updated versions of the target machine learning pipeline. The embodiment may extract a series of key features from detected versions of the target machine learning pipeline and cluster the detected versions of the target machine learning model pipeline by the extracted series of key features. The embodiment may identify a highest-quality version within each of a series of generated clusters. The embodiment may compute similarity scores for subsets of versions within each of the series of generated clusters. The embodiment may generate and output to a user, a visual representation of the series of generated clusters including version quality data and version similarity data.
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Patent Agency Ranking
公开(公告)号：US11947449B2
公开(公告)日：2024-04-02
申请号：US17811198
申请日：2022-07-07
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： Lei Gao , Jin Wang , A Peng Zhang , Kai Li , Jun Wang , Jing James Xu , Rui Wang , Xin Feng Zhu
CPC classification number: G06F11/3692 , G06F11/3688
Abstract: Embodiments of the present disclosure relate to a method, system and computer program product for semantic search based on a graph database. In some embodiments, a method is disclosed. According to the method, the user jobs of a user are obtained from a first software product. Based on the user jobs, target test cases are selected from a plurality of test cases associated with the first software product and a second software product. The target test cases are applied to the first software product and the second software product, and in accordance with a determination that a result of applying the target test cases satisfies a predetermined criterion, an instruction is provided to indicate migrating from the first software product to the second software product. In other embodiments, a system and a computer program product are disclosed.
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公开(公告)号：US20230359758A1
公开(公告)日：2023-11-09
申请号：US17661780
申请日：2022-05-03
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： Jin Wang , Lei GAO , A PENG ZHANG , Kai Li , Jun Wang , Xiao Ming Ma , Xin Feng Zhu , Geng Wu Yang
IPC: G06F21/62
CPC classification number: G06F21/6245
Abstract: The present disclosure relates to privacy protection in a search process. According to a method, a target emotion vector is extracted from a search interaction, the target emotion vector representing emotional information in the search interaction. Respective emotion distances between the target emotion vector and respective emotion vectors associated with a plurality of text clusters are determined. The plurality of text clusters is clustered from a dictionary of text elements. A first number of text clusters are selected from the plurality of text clusters based on the determined respective emotion distances. The first number of text clusters have emotion distances larger than at least one unselected text cluster among the plurality of text clusters. A plurality of confused search interactions are constructed for the search interaction based on the first number of text clusters, and the plurality of confused search interactions are performed.
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公开(公告)号：US20230052848A1
公开(公告)日：2023-02-16
申请号：US17398215
申请日：2021-08-10
Applicant: International Business Machines Corporation
Inventor： A PENG ZHANG , Lei Gao , Jin Wang , Jia Xing Tang , Kai Li , Geng Wu Yang , Zhen Liu
Abstract: An approach is provided in which the approach loads a machine learning model and a set of test case statistical data into a user system. The set of test case statistical data is based on a set of test cases corresponding to the machine learning model and includes a plurality of input parameter sets and a corresponding set of output quality measurements. The approach compares user data on the user system against the set of test case statistical data and identifies one of the plurality of input parameter sets to optimize the machine learning model based on the set of output quality measurements. The approach generates an optimized machine learning model using the machine learning model and the identified input parameter set at the user system.
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公开(公告)号：US20220091967A1
公开(公告)日：2022-03-24
申请号：US17027780
申请日：2020-09-22
Applicant: International Business Machines Corporation
Inventor： Jin Wang , Lei Gao , A PENG ZHANG , Si Er Han , Jing James Xu , Kai Li
Abstract: Test case selection methods are disclosed. A feature of a candidate test case and respective features of a set of test cases are extracted. The set of test cases is clustered into a plurality of clusters based on the respective features of the set of test cases. At least one cluster related to the candidate test case is determined from the plurality of clusters based on the feature of the candidate test case. At least one test case similar to the candidate test case is selected from a plurality of test cases included in the at least one cluster.
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公开(公告)号：US11151309B1
公开(公告)日：2021-10-19
申请号：US16934175
申请日：2020-07-21
Applicant: International Business Machines Corporation
Inventor： Lei Gao , Xin Feng Zhu , Kai Li , A Peng Zhang , Jia Xing Tang , Jin Wang
IPC: G06F17/00 , G06F40/169 , G06K9/46 , G06T11/60 , G06K9/62
Abstract: Embodiments of the present disclosure relate to screenshot-based memos. In an embodiment, a computer-implemented method is disclosed. The method comprises a monitoring displaying screen on a computing device for determining whether the displaying screen reaches a preset trigger condition. The method further comprises capturing a snapshot of the displaying screen in response to the displaying screen reaching the preset trigger condition. The method further comprises matching one or more screenshots comprised in one or more screenshot-based memos and the captured snapshot for obtaining a similarity degree. The method further comprises deploying the one or more screenshot-based memos on the displaying screen in response to the similarity degree meeting a preset similarity threshold. In other embodiments, a system and a computer program product are disclosed.
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