Patents by Inventor Ling Zhuo
Ling Zhuo 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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Publication number: 20230409421Abstract: First event data is obtained from a first computer system and second event data is obtained from a second computer system. A first shape of the first event data is identified, and a second shape of the second event data is identified. A shape similarity between the first shape and the second shape is calculated. The shape similarity is determined to be above a similarity threshold. Training features are generated from the first event data and the second event data based on the determining. The training features are input into an anomaly-detection model.Type: ApplicationFiled: June 20, 2022Publication date: December 21, 2023Inventors: Yi Dai, Ling Zhuo, Ying Cao, Yin Xia, Junfei Shen
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Patent number: 11762939Abstract: An approach is disclosed that determines an amount of time before a webpage is ready to use by a user by performing various actions. The approach captures a recording of the webpage from an invocation of the webpage for a period of time sufficient to load completely load the webpage with the capturing resulting in sequenced image frames. An AI system provides a loading point in the sequenced image frames based on an analysis of the frames input to the trained AI system. Image diversity and saturation measurements are calculated on consecutive image frames from the sequenced image frames resulting in an image change analysis. Native webpage events and times are detected from webpage characteristics gathered from the captured digital recording. The amount of time is then calculated based on the loading point from the AI system, the image change analysis; and the webpage events and their corresponding times.Type: GrantFiled: August 25, 2021Date of Patent: September 19, 2023Assignee: International Business Machines CorporationInventors: Ling Zhuo, Pei Pei Liang, Lin Yan Wu, Li Zhou, Yue Yang, Yun Bo Zhang, Tao Wen
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Patent number: 11729068Abstract: An approach is provided in which the approach captures a first user activity log of a first user accessing multiple systems and captures a set of second user activity logs of a set of second users accessing the multiple systems. The approach determines a set of system monitoring preferences based the first user activity log and the set of second user activity logs, and scores the multiple systems based on the set of system monitoring preferences. The approach generates a recommended system monitoring list based on the scored multiple systems, and transmits the recommended system monitoring list to the first user.Type: GrantFiled: September 9, 2021Date of Patent: August 15, 2023Assignee: International Business Machines CorporationInventors: Tian Jiao Zhang, Yuan Feng, Yan Yan Han, Su Li Hou, Xue Ying Zhang, Jing Xu, Ling Zhuo
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Publication number: 20230221847Abstract: An embodiment includes detecting an interface element and an element attribute of the interface element in a series of views of a user interface, and then after an update of the user interface, detecting a candidate element and a candidate element attribute in a series of views of the updated user interface. The embodiment then determines that the updated user interface lacks any errors using a decision tree that includes comparisons of all interface elements of the user interface to corresponding candidate elements of the updated user interface. The embodiment then generates an optimized decision tree based at least in part on an analysis of the comparisons of the user interface to the updated user interface resulting in a condition that allows for the determining of a lack of errors based on comparisons of a subset of the interface elements to corresponding candidate elements.Type: ApplicationFiled: January 13, 2022Publication date: July 13, 2023Applicant: International Business Machines CorporationInventors: Yuan Feng, Yan Yan Han, Ling Zhuo, Tian Jiao Zhang, Jing Xu, Xue Ying Zhang, SU LI HOU
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Publication number: 20230214454Abstract: An embodiment generates an initial set of training data from monitoring data. The initial set of training data is generated by combining outputs from a plurality of pretrained classifiers. The embodiment trains a new classification model using the initial set of training data to identify anomalies in monitoring data. The embodiment performs a multiple-level clustering of the data samples resulting in a plurality of clusters of sub-clusters of data samples, and generates a review list of data samples by selecting a representative data sample from each of the clusters. The embodiment receives an updated data sample from the expert review that includes a revised target classification for at least one of the data samples of the expert review list. The embodiment then trains another replacement classification model using a revised set of training data that includes the updated data sample and associated revised target classification.Type: ApplicationFiled: January 4, 2022Publication date: July 6, 2023Applicant: International Business Machines CorporationInventors: Ke Wei Wei, Jun Wang, Shuang YS Yu, Guang Ming Zhang, Yuan Feng, Yi Dai, Ling Zhuo, Jing Xu
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Publication number: 20230084737Abstract: An approach is provided in which the approach captures a first user activity log of a first user accessing multiple systems and captures a set of second user activity logs of a set of second users accessing the multiple systems. The approach determines a set of system monitoring preferences based the first user activity log and the set of second user activity logs, and scores the multiple systems based on the set of system monitoring preferences. The approach generates a recommended system monitoring list based on the scored multiple systems, and transmits the recommended system monitoring list to the first user.Type: ApplicationFiled: September 9, 2021Publication date: March 16, 2023Inventors: Tian Jiao Zhang, Yuan Feng, Yan Yan Han, SU LI HOU, Xue Ying Zhang, Jing Xu, Ling Zhuo
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Publication number: 20230063608Abstract: An approach is disclosed that determines an amount of time before a webpage is ready to use by a user by performing various actions. The approach captures a recording of the webpage from an invocation of the webpage for a period of time sufficient to load completely load the webpage with the capturing resulting in sequenced image frames. An AI system provides a loading point in the sequenced image frames based on an analysis of the frames input to the trained AI system. Image diversity and saturation measurements are calculated on consecutive image frames from the sequenced image frames resulting in an image change analysis. Native webpage events and times are detected from webpage characteristics gathered from the captured digital recording. The amount of time is then calculated based on the loading point from the AI system, the image change analysis; and the webpage events and their corresponding times.Type: ApplicationFiled: August 25, 2021Publication date: March 2, 2023Inventors: Ling Zhuo, Pei Pei Liang, Lin Yan Wu, Li Zhou, Yue Yang, Yun Bo Zhang, Tao Wen
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Publication number: 20220318666Abstract: A method is presented to facilitate the training of a very large number of machine-learning performance models used to detect anomalies in computing operations. The models are grouped together according to model type, and are allocated to different pods of a computing environment that is used to carry out the operations being monitored. Initial training of models in a group is carried out while monitoring resource usage, and a particular pod is selected for further training based on the resource usage. The pod selected for training preferably has a minimum change in resource usage before and after the initial training. A different pod can be selected for scoring the trained models. The pod selected for scoring preferably has a maximum resource usage during an initial scoring among all pods.Type: ApplicationFiled: March 30, 2021Publication date: October 6, 2022Inventors: Tong Luo, Yi Dai, Guang Ming Zhang, Bing Jiang Sun, Shun Xin Cao, Yan Chen, Ling Zhuo
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Patent number: 11301352Abstract: Ranking system metrics for monitoring by sorting members of a set of system metrics into correlation groups according to correlations among historic time series data, determining a sensitivity of the members of the set of system metrics, determining an importance of the members of the set of system metrics according to the correlation groups and sensitivity, and ranking the members of the set of system metrics according to the importance.Type: GrantFiled: August 26, 2020Date of Patent: April 12, 2022Assignee: International Business Machines CorporationInventors: Ling Zhuo, Yi Dai, Yin Xia, Ying Cao, Enzhong Wang
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Publication number: 20220066900Abstract: Ranking system metrics for monitoring by sorting members of a set of system metrics into correlation groups according to correlations among historic time series data, determining a sensitivity of the members of the set of system metrics, determining an importance of the members of the set of system metrics according to the correlation groups and sensitivity, and ranking the members of the set of system metrics according to the importance.Type: ApplicationFiled: August 26, 2020Publication date: March 3, 2022Inventors: Ling Zhuo, Yi Dai, Yin Xia, Ying Cao, Enzhong Wang