International Business Machines Corporation

Guang Qing Zhong

Kun Yan Yin

Zhuo Jp Cai

Yi Ming Wang

Wen Jie Wang

Dan Zhang

Zhong Fang Yuan

Tong Liu

Rong Fu

Yi Zhi Yao

Jian Dong Yin

He Li

Hong Bing Zhang

Kang Ed Zhang

De Shuo Kong

Hao Sheng

Quan Yuan

Chao Xin

Xin Tang

Qia Wang

An approach for extracting non-textual data from an electronic document is disclosed. The approach includes receiving a request to extract a file and converting the file into pixels. The approach creates a pixel map of the converted file and determines one or more density clusters of the pixel map based on image clustering method. Furthermore, the approach determines one or more coordinates of the one or more density clusters and determines one or more candidate information regions based on the one or more coordinates, density of the one or more density clusters. Finally, the approach extracts one or more textual data based on the one or more candidate information regions and outputs the extracted one or more textual data.

Extracting non-textual data from documents via machine learning

Embodiments of the present disclosure relate to environment monitoring and associated monitoring device, in which region-level environmental conditions are obtained and are detected by a plurality of sensors installed in a plurality of regions of a space enclosing electronic devices. Additionally, respective region priorities of the plurality of regions are determined based at least in part on the region-level environmental conditions, a region priority indicating a probability of occurrence of a risk event within a corresponding region. Furthermore, a movement path of a moveable monitoring device through the plurality of regions is determined based on the region priorities for detecting device-level environmental conditions associated with the electronic devices, and a moveable monitoring device and a system are disclosed.

Environment monitoring and associated monitoring device

A method, computer system, and a computer program product for analyzing visual defects is provided. The present invention may include generating a template image. The present invention may include capturing a test image. The present invention may include performing an image registration between the template image and the test image. The present invention may include generating a registered test image. The present invention may include performing an image difference analysis between the registered test image and the template image. The present invention may include generating a differential image. The present invention may include synthesizing the registered, differential image, and template image. The present invention may include generating a synthetic image. The present invention may include inputting the synthetic image into a multi-scale detection network. The present invention may include generating a defect map.

Determining image defects using image comparisons

Disclosed embodiments provide techniques for computerized technical support. A knowledge graph for a computer application is established. An input query from a user is processed to extract entities used as action identifiers. One or more nodes within the knowledge graph are identified, along with corresponding relationship edges leading to the nodes. When multiple candidate nodes are found that contain information relevant to the input query, a custom clarification statement is created based on the one or more identified relationship edges. The user provides answers to the clarification statement to narrow down which nodes contain the most relevant information. This process may continue, eliminating nodes based on user responses, until a single node remains, corresponding to an action identifier. The action identifier includes action description information that provides technical assistance to a user.

Dynamic workflow with knowledge graphs

Feedback is collected from a user during log-on to a system. The feedback from the user can be used to enhance a knowledge base. The feedback is required from the user in order for the user to gain access to the system.

Collecting user feedback through logon questions

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Beijing, China

Guang Qing Zhong