Abstract: The present invention provides a computer implemented method, a system, and a computer program product of identifying and analyzing the impact of an event associated with an entity on relationships of the entity. In an exemplary embodiment, the present invention includes storing data that identifies relationships with entities associated with the entity, based on data about the entity and data about the entities from at least one online website, storing data that identifies entity relationships, among the entity relationships identified in an entity relationship data structure, that are determined by the computer system to be affected by events associated with event categories, receiving data about events related to the entity, and outputting data related to a recommendation for a second entity among the entities associated with the entity, wherein the second entity corresponds to a most affected relationship, based on data associated with the second entity.

Abstract: A method, computer system, and a computer program product for analyzing a crowd using a plurality of images captured by an aerial drone is provided. The present invention may include determining a geographic area associated with the crowd. The present invention may also include partitioning the determined geographic area into a plurality of zones. The present invention may then include determining a flight path covering each zone within the plurality of zones. The present invention may further include receiving the plurality of images from the aerial drone. The present invention may also include analyzing the received plurality of images to identify a plurality of individuals associated with the crowd. The present invention may then include predicting a plurality of crowd characteristics based on the analyzed plurality of images. The present invention may further include performing an action in response to the predicted plurality of crowd characteristics.

Abstract: The present invention provides a computer implemented method, a system, and a computer program product of identifying and analyzing the impact of an event associated with an entity on relationships of the entity. In an exemplary embodiment, the present invention includes storing data that identifies relationships with entities associated with the entity, based on data about the entity and data about the entities from at least one online website, storing data that identifies entity relationships, among the entity relationships identified in an entity relationship data structure, that are determined by the computer system to be affected by events associated with event categories, receiving data about events related to the entity, and outputting data related to a recommendation for a second entity among the entities associated with the entity, wherein the second entity corresponds to a most affected relationship, based on data associated with the second entity.

Abstract: A method, computer system, and a computer program product for analyzing a crowd using a plurality of images captured by an aerial drone is provided. The present invention may include determining a geographic area associated with the crowd. The present invention may also include partitioning the determined geographic area into a plurality of zones. The present invention may then include determining a flight path covering each zone within the plurality of zones. The present invention may further include receiving the plurality of images from the aerial drone. The present invention may also include analyzing the received plurality of images to identify a plurality of individuals associated with the crowd. The present invention may then include predicting a plurality of crowd characteristics based on the analyzed plurality of images. The present invention may further include performing an action in response to the predicted plurality of crowd characteristics.

Abstract: A method, computer system, and a computer program product for analyzing a crowd using a plurality of images captured by an aerial drone is provided. The present invention may include determining a geographic area associated with the crowd. The present invention may also include partitioning the determined geographic area into a plurality of zones. The present invention may then include determining a flight path covering each zone within the plurality of zones. The present invention may further include receiving the plurality of images from the aerial drone. The present invention may also include analyzing the received plurality of images to identify a plurality of individuals associated with the crowd. The present invention may then include predicting a plurality of crowd characteristics based on the analyzed plurality of images. The present invention may further include performing an action in response to the predicted plurality of crowd characteristics.

Abstract: The present invention provides a computer implemented method, a system, and a computer program product of identifying and analyzing the impact of an event associated with an entity on relationships of the entity. In an exemplary embodiment, the present invention includes storing data that identifies relationships with entities associated with the entity, based on data about the entity and data about the entities from at least one online website, storing data that identifies entity relationships, among the entity relationships identified in an entity relationship data structure, that are determined by the computer system to be affected by events associated with event categories, receiving data about events related to the entity, and outputting data related to a recommendation for a second entity among the entities associated with the entity, wherein the second entity corresponds to a most affected relationship, based on data associated with the second entity.

Abstract: The present invention provides a computer implemented method, a system, and a computer program product of identifying and analyzing the impact of an event associated with an entity on relationships of the entity. In an exemplary embodiment, the present invention includes storing data that identifies relationships with entities associated with the entity, based on data about the entity and data about the entities from at least one online website, storing data that identifies entity relationships, among the entity relationships identified in an entity relationship data structure, that are determined by the computer system to be affected by events associated with event categories, receiving data about events related to the entity, and outputting data related to a recommendation for a second entity among the entities associated with the entity, wherein the second entity corresponds to a most affected relationship, based on data associated with the second entity.

Abstract: An approach, executed by one or more computer processors, to determine a sentiment based, at least in part, on one or more statements from one or more sources in a plurality of documents for a proceeding. The approach includes the one or more computer processors predicting an outcome of the proceeding, based, at least in part, on the sentiment.

Abstract: Machine logic that automatically detects natural language processing (NLP) system annotation errors and correspondingly updates NLP annotators to prevent future erroneous annotations by performing the following steps: (i) determining that a first annotation error has occurred in an annotation of a corpus by the natural language processing system; (ii) generating a candidate set of annotation correction actions, where each annotation correction action of the set is adapted to prevent an occurrence of an error similar to the first annotation error by the natural language processing system; (iii) selecting an annotation correction action from the candidate set of annotation correction actions, based, at least in part, on a set of annotation correction confidence characteristics; and (iv) automatically applying the selected annotation correction action to the natural language processing system.

Abstract: Machine logic that automatically detects natural language processing (NLP) system annotation errors and correspondingly updates NLP annotators to prevent future erroneous annotations by performing the following steps: (i) determining that a first annotation error has occurred in an annotation of a corpus by the natural language processing system; (ii) generating a candidate set of annotation correction actions, where each annotation correction action of the set is adapted to prevent an occurrence of an error similar to the first annotation error by the natural language processing system; (iii) selecting an annotation correction action from the candidate set of annotation correction actions, based, at least in part, on a set of annotation correction confidence characteristics; and (iv) automatically applying the selected annotation correction action to the natural language processing system.