Abstract: A computer-implemented method includes identifying a webpage comprising a set of user interface (UI) elements, analyzing the set of user UI elements to identify a set of interactable elements, classifying the elements of the set interactable elements as either focusable or not focusable, extracting features from source code corresponding to interactable elements of the set of interactable elements classified as focusable, and building an accessibility issue detection model using the extracted features from source code corresponding to focusable interactable elements as training data. The method may further include extracting features from source code corresponding to interactable elements classified as not focusable and updating the accessibility issue detection model using the extracted features from source code corresponding to interactable elements which are not focusable as training data.

Abstract: A computer-implemented method, according to one approach, includes: receiving a request to add a subset of participants on a group call to a private communication channel. The group call includes a shared communication channel extending between the participants, the shared communication channel being configured to exchange information between the participants. The method further includes evaluating statuses of the participants in the subset. Moreover, in response to determining that the participants in the subset are not already included on a different private communication channel, and that the participants in the subset are not actively being added to a different private communication channel, the subset of participants are added to the private communication channel.

Abstract: A method for improving the accuracy of speech recognition is disclosed. In one embodiment, such a method receives speech input from a user. The method further receives background inputs describing at least one of a webpage and an application from which the speech input was received. The method determines a language associated with the speech input and determines a weight and confidence level for each of the background inputs. A score is calculated for each of the background inputs based on the corresponding weight and confidence level. The method determines textual candidates for output in response to the speech input and ranks the textual candidates using a function that takes into account the scores and/or confidence levels of the background inputs. The textual candidate with the highest ranking may be returned to the user. A corresponding system and computer program product are also disclosed.

Abstract: A computer-implemented method, according to one embodiment, includes: receiving an initial sequence of operational instructions configured to update software programming in an electronic device. Contradicting ones of the operational instructions in the initial sequence are identified, and differences between the contradicting operational instructions are compared. As a result, the contradicting operational instructions are rectified by modifying the initial sequence of operational instructions. The software programming in the electronic device is also updated by implementing the modified sequence of operational instructions.

Abstract: A computer-implemented method, according to one embodiment, includes determining a domain and category information from metadata associated with a first webpage. The method further includes determining component types, hierarchies and grouping relationships for a plurality of text elements on the first webpage and constructing context information for the text elements. Word vectors are calculated based on the grouping relationships and the context information, and text feature types of the text elements are extracted based on the word vectors and the context information. The method further includes using the extracted text feature types to determine a re-ordering of a translation of the text elements. A computer program product, according to another embodiment, includes a computer readable storage medium having program instructions embodied therewith. The program instructions are readable and/or executable by a computer to cause the computer to perform the foregoing method.

Abstract: From an input image comprising a portion of text, the portion of text is extracted. The portion of text comprises text in a first natural language. The input image is classified into a candidate scene within a set of predefined scenes. The candidate scene is scored according to a quality measure. Using a predefined scene parameter of the scored candidate scene, the portion of text is translated. In the input image, the portion of text is replaced. with the translated portion of text.

Abstract: A method for correcting translation errors when performing GUI globalization testing is disclosed. In one embodiment, such a method takes a screenshot of a graphical user interface (GUI). The method further enables a user to select text in the screenshot. In certain embodiments, one or more of the text and coordinates associated with the text are stored in picture attributes associated with the screenshot. In response to the selection, the method automatically retrieves a file in which at least some portion of the text is contained. The method automatically locates, within the file, the portion, and enables the user to update the portion in the file in order to update corresponding text in the graphical user interface. In certain embodiments, the method provides a probability percentage associated with the file that indicates a probability that the text in the file links to the selected text in the graphical user interface.

Abstract: A method, computer system, and a computer program product are provided for a restoring missing content to a user that was absent during a portion of a live event. The process will identify the absence period and that is being participated by a user and obtains extracted information relating to the user that was previously gathered from a variety of sources including past user interactions and a user profile. This information is further analyzed and prioritized according to user interest priority determined by the extracted information. This information is categorized into a first set of domains. Information provided during the absence of the user will also be captured and categorized into a second set of domain categories. An intersection between the first and second set of domain categories will be found and prioritized by user interest. This will be presented to the user upon user's return.

Abstract: A computer-implemented method, according to one embodiment, includes using a trained semantic consistency model to determine a semantic consistency of contents of two screenshots. The trained semantic consistency model bases the semantic consistency on dimensions including: a linguistic comparison of the contents, an image comparison of the contents and a text location comparison of the contents. The method further includes outputting the determined semantic consistency for display on a user device. A computer program product, according to another embodiment, includes a computer readable storage medium having program instructions embodied therewith. The program instructions are readable and/or executable by a computer to cause the computer to perform the foregoing method. A system, according to another embodiment, includes a processor, and logic integrated with the processor, executable by the processor, or integrated with and executable by the processor.

Abstract: Aspects of the present disclosure relate generally to UI automation in RPA and, more particularly, to automation of contextual UI element identification by RPA robots. For example, a computer-implemented method includes: receiving, by a processor set, user interface context identification information of attributes of user interface elements in user interface code of an application; constructing, by the processor set, a model of the attributes of the user interface elements including an attribute indicating functionality of at least one user interface element; obtaining from the model of the attributes of the user interface elements an identification of the at least one user interface element referenced in an action command for performing the functionality of the at least one user interface element in robotic process automation code; and storing, by the processor set, the model of the attributes of the user interface elements in persistent storage.

Abstract: From an input image comprising a portion of text, the portion of text is extracted. The portion of text comprises text in a first natural language. The input image is classified into a candidate scene within a set of predefined scenes. The candidate scene is scored according to a quality measure. Using a predefined scene parameter of the scored candidate scene, the portion of text is translated. In the input image, the portion of text is replaced. with the translated portion of text.

Abstract: Computer-implemented methods, computer program products, and computer systems are provided. A method includes generating a running result matrix for a plurality of batch jobs, indicating corresponding running results for respective processing actions in batch jobs of the plurality of batch jobs. The method further includes obtaining an internal dependency matrix for the plurality of batch jobs, indicating corresponding dependencies between respective processing actions within a batch job of the plurality of batch jobs. The method further includes calculating a recovery matrix for the plurality of batch jobs based, at least in part, on the running result matrix and the internal dependency matrix, the recovery matrix indicating corresponding recovery actions for respective processing actions in batch jobs of the plurality of batch jobs. The method further includes executing failover management for one or more batch jobs based, at least in part, on the calculated recovery matrix.

Abstract: Computer-implemented methods, computer program products, and computer systems are provided. A method includes generating a running result matrix for a plurality of batch jobs, indicating corresponding running results for respective processing actions in batch jobs of the plurality of batch jobs. The method further includes obtaining an internal dependency matrix for the plurality of batch jobs, indicating corresponding dependencies between respective processing actions within a batch job of the plurality of batch jobs. The method further includes calculating a recovery matrix for the plurality of batch jobs based, at least in part, on the running result matrix and the internal dependency matrix, the recovery matrix indicating corresponding recovery actions for respective processing actions in batch jobs of the plurality of batch jobs. The method further includes executing failover management for one or more batch jobs based, at least in part, on the calculated recovery matrix.

Abstract: The present disclosure relates to a method and system for deploying user interface elements on a screen which has broken-faulty regions on the screen. One or more broken-faulty regions are detected on the screen. At least a part of the normal regions on the screen is determined to be a region for displaying at least a part of one or more user interface elements which are related to the one or more broken-faulty regions. The at least a part of the one or more user interface elements are deployed on the screen based on the result of the determining.

Abstract: The present disclosure relates to a method and system for deploying user interface elements on a screen which has broken-faulty regions on the screen. One or more broken-faulty regions are detected on the screen. At least a part of the normal regions on the screen is determined to be a region for displaying at least a part of one or more user interface elements which are related to the one or more broken-faulty regions.