Abstract: Detecting duplicate tables by converting relational tables to knowledge graphs; and mapping nodes in the knowledge graphs to sources in the relational tables. The method may further include applying graph matching to the knowledge graphs; and assessing degree of matching between matched knowledge graphs.

Abstract: Detecting duplicate tables by converting relational tables to knowledge graphs; and mapping nodes in the knowledge graphs to sources in the relational tables. The method may further include applying graph matching to the knowledge graphs; and assessing degree of matching between matched knowledge graphs.

Abstract: Techniques are described with respect to a system, method, and computer product for generating relevance alerts. An associated method includes analyzing a multi-party discussion based on a generated profile associated with a user and assigning at least one relevance value associated with the user to the multi-party discussion based on the analysis and an amount of multi-party discussion participation associated with the user. The method further includes generating an alert for the user to participate in the multi-party discussion in response to determining the relevance value exceeding a relevance threshold associated with the multi-party discussion.

Abstract: One or more unmanned aerial vehicles (UAVs) having a ground map stored therein are employed to assist an aircraft in landing at an airfield. A determination is made that the aircraft requires assistance landing at the airfield. Instructions are sent to the one or more UAVs to synchronize a flight path with the aircraft. The one or more UAVs receive sensor data regarding conditions surrounding the aircraft and the airfield. The aircraft is controlled by the one or more based upon the ground map, the flight characteristic profile, and the group map. The controlling of the aircraft by the one or more UAVs is discontinued upon the aircraft landing at the airfield.

Abstract: A method, computer system, and a computer program product for historical image search is provided. The present invention may include receiving an image search criteria. The present invention may also include generating a composite image search query based on the received image search criteria. The present invention may further include searching for a matching historical image based on the generated composite image search query. The present invention may also include returning a historical image search result.

Abstract: A method, computer program product and/or system that performs the following operations (not necessarily in the following order): (i) receiving an input image (for example, a photograph) that includes a image portion and “caption text” (for example, an overlaid caption or some text that is captured in a photograph); (ii) extracting the caption text from the input image; (iii) extracting a plurality of image attributes relating to the caption text and image portion; (iv) applying sentiment analysis to the plurality of image attributes to select a selected font determining a sentiment associated with the plurality of image attributes; and (iv) generating an output image that includes the image portion of the input image and the caption text presented in the selected font.

Abstract: A method includes preparing key actions in a process design document (PDD) from historical PDD documents by tokenizing the PDD with part-of-speech (POS) grammar against key verbs and phrases, extracting automation unit pairs from the historical process documents to map the automation unit pairs with the key verbs and phrases, constructing a set of automation tasks against one or more of the key verbs and phrases, coupling different process models with domain verbs for the phrases to mark one or more of the automation unit pairs as actions against one or more of the key verbs, constructing a tree-like mapping where each key action points to different actions in a target specific automation language, and defining a vocabulary interface of a domain specific language (DSL) by using the key actions and phrases.

Abstract: An embodiment includes generating, responsive to detecting a communication attempt made by a caller, first request data indicative of a first connection request from a caller communication terminal associated with the caller to a callee communication terminal associated with a callee. The embodiment appends caller context data to the first request data, where the caller context data is based on Internet of Things (IoT) data received from an IoT device associated with the caller. The embodiment detects a connection failure resulting from the connection request. The embodiment generates callee context data based on IoT data received from an IoT device associated with the callee, and then selects a trusted contact from among a list of trusted contacts associated with the callee and generates second request data indicative of a second connection request from the caller communication terminal to a contact communication terminal associated with the trusted contact.

Abstract: Various systems and methods are presented regarding automatically generating a document for a particular topic, and further utilizing an algorithm to automatically identify information in a resource that pertains to the topic. The document can be a purpose-specific document, created by a template configured to combine data fields to build the document. Each data field can be subject-matter specific with an associated algorithm. The algorithm can be trained to recognize and extract content that potentially meets the subject matter of the data field. The data field can be populated with the content. Subsequent editing of the content populating the data field can be monitored to determine an effectiveness of the algorithm to identify data of interest in the data repository. In the event of low success, the algorithm can be retrained. Further, the document can be regenerated if an algorithm is retrained, new information added to the repository, etc.

Abstract: Process transformation can include mapping, by a first machine learning model, predetermined key performance indicators (KPIs) to a discovered process model. For each of the KPIs, a KPI gap and a KPI impact score can be determined. For each of the KPIs, a KPI-level enhancement potential value based on the KPI gap and KPI impact score of each KPI can be determined. Based on the KPI-level enhancement potential value of each of the KPIs, a process value debt (PVD) can be generated. Responsive to the PVD exceeding a predetermined threshold, a process transformation recommendation generated by a second machine learning model can be outputted to identify at least one modification to the process that is likely to reduce the PVD.

Abstract: Provided is a method, computer program product, and system for mitigating user dissatisfaction with a product. A processor may collect a first set of user interaction data and a first set of user sentiment data related to the product. The processor may generate a user profile for the user, including a satisfaction threshold for using the product based in part on the first set of user interaction data and the first set of user sentiment data. The processor may monitor a second set of user interaction data and a second set of user sentiment data. The processor may compare the second set of user interaction data and the second set of user sentiment data to the satisfaction threshold and determine that the user is experiencing dissatisfaction with the product when the satisfaction threshold has been exceeded. In response, the processor may output an action to reduce dissatisfaction of the user.

Abstract: In an approach for enhancing an experience of a user listening to and/or watching an audio-visual content by modifying future audio and/or video frames of the audio-visual content, a processor captures a set of sensor data from an IoT device worn by the first user. A processor analyzes the set of sensor data to generate one or more connotations by converting the emotion using an emotional vector analytics technique and a supervised machine learning technique. A processor scores the one or more connotations on a basis of similarity between the emotion exhibited by the first user and an emotion expected to be provoked by a second user. A processor determines whether a score of the one or more connotations exceeds a pre-configured threshold level. Responsive to determining the score does not exceed the pre-configured threshold level, a processor generates a suggestion for the producer of the audio-visual content.

Abstract: In an approach for enhancing an experience of a user listening to and/or watching an audio-visual content by modifying future audio and/or video frames of the audio-visual content, a processor captures a set of sensor data from an IoT device worn by the first user. A processor analyzes the set of sensor data to generate one or more connotations by converting the emotion using an emotional vector analytics technique and a supervised machine learning technique. A processor scores the one or more connotations on a basis of similarity between the emotion exhibited by the first user and an emotion expected to be provoked by a second user. A processor determines whether a score of the one or more connotations exceeds a pre-configured threshold level. Responsive to determining the score does not exceed the pre-configured threshold level, a processor generates a suggestion for the producer of the audio-visual content.

Abstract: Techniques are described with respect to a system, method, and computer product for generating relevance alerts. An associated method includes analyzing a multi-party discussion based on a generated profile associated with a user and assigning at least one relevance value associated with the user to the multi-party discussion based on the analysis and an amount of multi-party discussion participation associated with the user. The method further includes generating an alert for the user to participate in the multi-party discussion in response to determining the relevance value exceeding a relevance threshold associated with the multi-party discussion.

Abstract: A method for receiving a historical incident data set with the historical incident data set including a plurality of data records, for each given data record of the plurality of data records, applying a causal analysis algorithm to determine a set of causal factor(s) for the historical instance of an incident corresponding to the given data record to obtain a problems and solutions data set, and automatically, and by machine logic, generating a chatbot based, at least in part, on the problems and solutions data set.

Abstract: An illustrative resolution is generated using a computer for a reported operational issue while using a computer system. A learning model is developed using the computer to facilitate resolving an operational error of a computer system. The learning model can include generating an error report, based on tracking user inputs into a computer system and a plurality of state transitions of the computer system, respectively, when the operational error is not resolved by the user inputs. An error screenshot for each operational step associated with the user inputs is generated. A state transition is cross referenced to a corresponding operational step, and to a best practice in a user's manual, respectively. A deviation of an operational step from a best practice in the user's manual, respectively, is generated. An error screenshot is marked illustratively to show the deviation from the best practice in comparison to the operational step.

Abstract: A client device can receive, from a data processing system, first data, the first data selected by the data processing system based on second data generated by at least one IoT device with which the client device is associated, and the first data indicating at least one advertisement. The client device can access the at least one advertisement using the first data indicating the at least one advertisement. The client device can add the at least one advertisement to the content accessed by the client device. The client device can present the content with the at least one advertisement added to the content.

Abstract: A method, computer system, and a computer program product for historical image search is provided. The present invention may include receiving an image search criteria. The present invention may also include generating a composite image search query based on the received image search criteria. The present invention may further include searching for a matching historical image based on the generated composite image search query. The present invention may also include returning a historical image search result.

Abstract: Embodiments of the invention are directed to a computer-implemented method of performing an electronic search. The computer-implemented method includes receiving, using a processor, a composite electronic image including a plurality of electronically identifiable objects, wherein the composite electronic image is associated with a user. The processor is used to segment the composite electronic image into sub-images by providing at least one of the sub-images for each of the plurality of electronically identifiable objects. For each of the sub-images, the processor is used to perform personalized sub-image search operations. The personalized sub-image search operations include selecting a sub-image-to-be-searched from among the sub-images; associating the sub-image-to-be-searched with personalized metadata of the user; and searching, based at least in part on the personalized metadata of the user, a database to return a set of search images.

Abstract: A method for receiving a historical incident data set with the historical incident data set including a plurality of data records, for each given data record of the plurality of data records, applying a causal analysis algorithm to determine a set of causal factor(s) for the historical instance of an incident corresponding to the given data record to obtain a problems and solutions data set, and automatically, and by machine logic, generating a chatbot based, at least in part, on the problems and solutions data set.