Abstract: A method selectively activates a resource to accommodate an advanced emotion. A supervisor computer receives a first piece of content, and then applies an emotion classifier to the first piece of content in order to create a first concept/emotion/sentiment/time tuple. The supervisor computer creates a second concept/emotion/sentiment/time tuple for a second piece of content, and compares the first and second tuples. If the concept in the first piece of content matches the concept in the second piece of content but that at least one of the emotion, sentiment, and time of the first piece of content does not match the emotion, sentiment, and time of the second piece of content, the supervisor computer determines that the emotion of the second piece of content is an advanced emotion that is not expressed by the first or second pieces of content, and activates a resource that accommodates the advanced emotion.

Abstract: Methods and systems for best-fitting meeting time prediction by ad-hoc ensemble creation for personalized classification with a group scope are disclosed. A computer-implemented method includes: receiving, by a computing device, a request to determine a timeslot for a meeting, the request including a plurality of invitees and information about a meeting requester; reading, by the computing device, for each of the plurality of invitees, information about currently scheduled meetings and a profile including a weight assigned to the meeting requester; determining, by the computing device, for each of a plurality of candidate timeslots, an ensemble value for the candidate timeslot based on the information about the currently scheduled meetings and the weight assigned to the meeting requester for each of the plurality of invitees; and selecting, by the computing device, the timeslot for the meeting based on the ensemble values for the candidate timeslots.

Abstract: A method selectively activates a resource to accommodate an advanced emotion. A supervisor computer receives a first piece of content, and then applies an emotion classifier to the first piece of content in order to create a first concept/emotion/sentiment/time tuple. The supervisor computer creates a second concept/emotion/sentiment/time tuple for a second piece of content, and compares the first and second tuples. If the concept in the first piece of content matches the concept in the second piece of content but that at least one of the emotion, sentiment, and time of the first piece of content does not match the emotion, sentiment, and time of the second piece of content, the supervisor computer determines that the emotion of the second piece of content is an advanced emotion that is not expressed by the first or second pieces of content, and activates a resource that accommodates the advanced emotion.