International Business Machines Corporation

Zhe Yan

Xiao Long Chen

Rong Zhao

Zhuo Zhao

Na Lv

Li Li Guan

Yun Zhai

Ke Zhang

Li Bo Zhang

Fabian F Morgan

Hao Jia Li

Xi Ning Wang

Chuan Yang

Danny Y Chen

Sarah White Eagle

Dan Dan Zheng

Yuan Jin

David Louis Kaminsky

Zheng Zhao

Jing Jing Zhang

Lei He

Bo Wen Wei

Jian Wang

Jian Ding

Chen Hui Xu

Peng Ji

He Huang

Guo Qiang Hu

Yong Hu

Jing Zhang

Liya Fan

Chen Tian

Peng Tang

Li Niu

Hua Fu

Hao Xiang Wu

Embodiments relate to graph-based design mapping and function route generation. A computer-implemented method includes analyzing first user interfaces and second user interfaces to identify features of each user interface, where the second user interfaces include at least one change to the first user interfaces. A first graph representing the features of the first user interfaces and a second graph representing the features of the second user interfaces are generated. A function mapping is determined based on a similarity calculation between the first graph and the second graph. A node that satisfies an influence threshold is recommended to do limited manual labeling. The function mapping is updated based on the labeling. A visualization of the function mapping is created between the first user interfaces and the second user interfaces. Function route generation can be performed.

Graph-based design mapping and function route generation

An embodiment for detecting anomalous data using dependency modeling. The embodiment may, within a target data environment, identify references between data contained in one or more data files. The embodiment may determine dependency relationships between data fields in the data contained in the one or more data files. The embodiment may construct computational graphs depicting the determined dependency relationships as series of related data fields. The embodiment may identify a series of associated computational graphs within the constructed computational graphs. The embodiment may calculate abnormality degree values for each of the data fields within the constructed computation graphs. The embodiment may, in response to detecting an anomalous data field having a calculated abnormality degree value above a threshold value, calculating contribution values for a series of associated component data fields to identify a root cause for the detected anomalous data field.

Detecting temporal anomalous data using dependency modeling

An approach for assisting software developers to fill the data gap and reproducing client application issue using reported reproducing steps is disclosed. The approach involves constructing service request/response sequence (from the developer's side based on the limited data) from customer's reproducing steps and developer's running inspection result and perform UI-service mapping, redirecting service call to data simulator which replay the service request and response, and adjusting service response with multiple data sources and policies. Lastly, the approach can transform the issue to an automatic test script with the service response in a mockup function (e.g., can be used to extend test data and enhance test cases).

Reproduction client application issue based on layered data replay

A computer-implemented method includes: extracting, by one or more processors, media data from an information technology ticket; extracting, by one or more processors, a plurality of data elements from the media data; and generating, by one or more processors, a ticket knowledge graph based on the plurality of data elements, wherein a node of the ticket knowledge graph represents a data element, and an edge between a first node and a second node in the ticket knowledge graph represents a correlation between a first data element represented by the first node and a second data element represented by the second node.

Ticket knowledge graph enhancement

Aspects of the present disclosure relate to support content generation. An issue description is received from a user. A software feature associated with the issue description is identified using a trained classification model. A base image associated with the software feature is obtained. The base image is modified to add information indicated in the issue description, wherein the modified base image is generated support content. The generated support content is transmitted.

User support content generation

A method, a computer program product, and a computer system guide a user through dimensional relationships. The method includes receiving a plurality of images of a unit of a perspective of a user. When a number of corresponding three-dimensional points between a current image and a previous image is less than a registration threshold to perform a three-dimensional registration operation, the method includes performing a three-dimensional data augmentation operation based on two-dimensional data from the current image and the previous image to generate extended corresponding three-dimensional points. The method includes determining a three-dimensional transform function between the current image and the previous image based on the extended corresponding three-dimensional points. The method includes generating annotations to be shown for the unit in the current image based on the three-dimensional transform function, the annotations being shown as a virtual rendering in a mixed reality environment viewed by the user.

Self guidance based on dimensional relationship

A method, computer system, and a computer program product for AR guidance is provided. The present invention may include detecting a plurality of objects in a video recording associated with completing a task. The present invention may include generating a plurality of three-dimensional (3D) object models based on scanning a plurality of real objects in a task space. The present invention may include matching the detected plurality of objects in the video recording with the generated plurality of 3D object models representing the plurality of real objects in the task space. The present invention may include generating, based on the video recording, an augmented reality (AR) guidance model for completing the task, wherein the generated AR guidance model replaces the detected plurality of objects in the video recording with the generated plurality of 3D object models representing the plurality of real objects in the task space.

Transforming asset operation video to augmented reality guidance model

A method, system and computer program product for improving photographic results by composition analysis using deep-learning neural networks, by: detecting one or more objects in a camera view; classifying the objects to make one or more composition recommendations; and displaying the composition recommendations in the camera view, wherein the camera view is aligned with one of the composition recommendations to take a picture.

Photographic results by composition analysis using deep learning neural networks

In one implementation, a first access behavior is determined. The first access behavior is for accessing a first dataset associated with a first tenant of a storage system, and the first dataset is stored in a first data node in the storage system. A second access behavior is determined. The second access behavior is for accessing a data entry that is to be added into a second dataset associated with a second tenant of the storage system, and the second dataset is stored in at least one data node in the storage system. In response to a deviation between the first access behavior and second access behavior being above a predefined threshold, the data entry is stored into the first data node.

Data management for multi-tenancy

Scheduling automated visual inspection tasks includes capturing an image of a component to be inspected. A visual inspection model is formed with a model engine as a composite model of utility modules and functional modules to perform visual inspection of the image of the component. An abstract processing workflow of the visual inspection model is derived with a scheduler including dependencies between the utility modules and the functional modules. Performance of each of the functional modules is profiled with the scheduler by testing performance with available hardware resources to produce a performance profile. Parallel instances of each of the functional modules in a branch of the abstract processing workflow are scheduled with the scheduler according to the dependencies and the performance profiles. An indication of defects in the component is produced by processing the visual inspection model according to the scheduled functional modules.

Flexible visual inspection model composition and model instance scheduling

A method, a computer program product, and a computer system for determining a location using street view images. A mobile device obtains an image captured by the mobile device, obtains a set of street view images, and obtains a first graph of the image captured by the mobile device and a plurality of second graphs of the set of the street view images. The first graph includes nodes representing interest points in the image captured by the mobile device, and the plurality of the second graphs includes nodes representing interest points in the set of the street view images. The mobile device determines a location of the mobile device, based on relevance between the first graph and the plurality of the second graphs.

Location determination using street view images

An approach is provided for synchronizing elements in files across a technical environment. In one embodiment, a processor obtains a first change to a first file. The processor also obtains data identifying a second file. The processor determines if the change is supported by a data library in a pre-defined list of data sources. The processor analyzes the data library to determine a type of the change. The processor applies the type of the change to the second file.

Dynamically synching elements in file

Embodiments of the present invention relate to a method, device and computer program product for container deployment. By comparing the target libraries required by a target container to be deployed and the libraries that have been loaded on the candidate hosts, the costs of deploying the target container on the candidate hosts can be estimated. Then a target host is selected from among the plurality of candidate hosts based on the determined costs.

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Beijing, China

Zhe Yan