Abstract: Using a logistic regression classification model executing on a processor, a topic is classified into an interaction type in a set of predefined interaction types. A set of documents corresponding to the topic is extracted from a document repository. Using a generative adversarial model executing on a processor, a sentiment corresponding to a reaction to a previous presentation is scored, the scoring resulting in a scored sentiment. Using a trained attention layer model, the interaction type, the set of documents, and the scored sentiment are weighted, the weighting generating a weighted interaction type, a weighted set of documents, and a weighted scored sentiment. Using a natural language generation transformer model executing on the processor, a document in the weighted set of documents is weighted according to the weighted interaction type and the weighted scored sentiment.

Abstract: A computer-implemented method and system for autonomic cloud to edge compute allocations in a sports fantasy league trade transaction. The computer implemented method includes, in one embodiment, calculating, based on an expected return associated with each player on each of a plurality of teams in a fantasy sports league, a valuation for each player. An embodiment includes determining a positional need for each of the plurality of teams in the fantasy sports league, and determining, based on the valuation for each player and the positional need for each team, one or more players to include in a trade with another team of the plurality of teams.

Abstract: Using a first trained generative adversarial network, a first multimedia content is transformed into a text description of the first multimedia content. The text description is adjusted according to a constraint using a trained attention layer, the adjusting creating an adjusted text description. Using a trained model, the adjusted text description is transformed into a second multimedia content, the second multimedia content comprising an adjustment of the first multimedia content according to the constraint.

Abstract: Using a sentiment analysis model, a reaction to a presentation of a first content is measured. Using the first content and the reaction, a content generation parameter is determined. Using a first content generation model and the content generation parameter, second content corresponding to the first content is generated. Using a second content generation model and the content generation parameter, third content corresponding to the first content is generated. The first content is adjusted by combining the first content with the second content and the third content, the adjusting resulting in an adjusted content.

Abstract: An embodiment calculates a point of view (POV) value for a subportion of an item of media content, including evaluating user inputs related to an automatically detected POV of the subportion of the item. The embodiment also calculates a non-factual cost for the subportion of the item indicative of an amount of the subportion of the item that lacks support in a fact-based corpora. The embodiment also performs a cascaded summarization process comprising generating a summary of the item using the subportion of the item and a summarization technique, analyzing the summary using a fact-checking algorithm to determine whether the summary satisfies a factual score threshold, and performing a next iteration of the cascaded summarization process while the summary fails to satisfy the factual score threshold. The embodiment also communicates a summary satisfying the factual score threshold to a user device.

Abstract: Using a sentiment analysis model, a reaction to a presentation of a first content is measured. Using the first content and the reaction, a content generation parameter is determined. Using a first content generation model and the content generation parameter, second content corresponding to the first content is generated. Using a second content generation model and the content generation parameter, third content corresponding to the first content is generated. The first content is adjusted by combining the first content with the second content and the third content, the adjusting resulting in an adjusted content.

Abstract: Using a logistic regression classification model executing on a processor, a topic is classified into an interaction type in a set of predefined interaction types. A set of documents corresponding to the topic is extracted from a document repository. Using a generative adversarial model executing on a processor, a sentiment corresponding to a reaction to a previous presentation is scored, the scoring resulting in a scored sentiment. Using a trained attention layer model, the interaction type, the set of documents, and the scored sentiment are weighted, the weighting generating a weighted interaction type, a weighted set of documents, and a weighted scored sentiment. Using a natural language generation transformer model executing on the processor, a document in the weighted set of documents is weighted according to the weighted interaction type and the weighted scored sentiment.

Abstract: A computer-implemented method and system for autonomic cloud to edge compute allocations in a sports fantasy league trade transaction. The computer implemented method includes, in one embodiment, calculating, based on an expected return associated with each player on each of a plurality of teams in a fantasy sports league, a valuation for each player. An embodiment includes determining a positional need for each of the plurality of teams in the fantasy sports league, and determining, based on the valuation for each player and the positional need for each team, one or more players to include in a trade with another team of the plurality of teams.

Abstract: A computer-implemented method and system for autonomic cloud to edge compute allocations in a sports fantasy league trade transaction. The computer implemented method includes, in one embodiment, calculating, based on an expected return associated with each player on each of a plurality of teams in a fantasy sports league, a valuation for each player. An embodiment includes determining a positional need for each of the plurality of teams in the fantasy sports league, and determining, based on the valuation for each player and the positional need for each team, one or more players to include in a trade with another team of the plurality of teams.

Abstract: Using a first trained generative adversarial network, a first multimedia content is transformed into a text description of the first multimedia content. The text description is adjusted according to a constraint using a trained attention layer, the adjusting creating an adjusted text description. Using a trained model, the adjusted text description is transformed into a second multimedia content, the second multimedia content comprising an adjustment of the first multimedia content according to the constraint.

Abstract: One or more computer processors create a user-event localization model for an identified remote audience member in a plurality of identified remote audience members for an event. The one or more computer processors generate a virtual audience member based the identified remote audience member utilizing a trained generated adversarial network and one or more user preferences. The one or more computer processors present the generated virtual audience member in a location associated with the event. The one or more computer processors dynamically adjust a presented virtual audience member responsive to one or more event occurrences utilizing the created user-event localization model.

Abstract: One or more computer processors create a user-event localization model for an identified remote audience member in a plurality of identified remote audience members for an event. The one or more computer processors generate a virtual audience member based the identified remote audience member utilizing a trained generated adversarial network and one or more user preferences. The one or more computer processors present the generated virtual audience member in a location associated with the event. The one or more computer processors dynamically adjust a presented virtual audience member responsive to one or more event occurrences utilizing the created user-event localization model.

Abstract: An embodiment calculates a point of view (POV) value for a subportion of an item of media content, including evaluating user inputs related to an automatically detected POV of the subportion of the item. The embodiment also calculates a non-factual cost for the subportion of the item indicative of an amount of the subportion of the item that lacks support in a fact-based corpora. The embodiment also performs a cascaded summarization process comprising generating a summary of the item using the subportion of the item and a summarization technique, analyzing the summary using a fact-checking algorithm to determine whether the summary satisfies a factual score threshold, and performing a next iteration of the cascaded summarization process while the summary fails to satisfy the factual score threshold. The embodiment also communicates a summary satisfying the factual score threshold to a user device.

Abstract: An embodiment of the invention may include a method, computer program product, and computer system for managing a machine learning algorithm. The embodiment may include a computing device that distributes a first algorithm to a plurality of computing devices. The embodiment may include updates to the first algorithm, to create a second algorithm, by a first device of the plurality of computing devices. The first device is grouped with other devices in a first cluster of devices of the plurality of computing devices. The first cluster of computing devices comprises more than one computing device. Updating the first algorithm is performed based on information shared amongst the first cluster of devices.

Abstract: A computer-implemented method and system for autonomic cloud to edge compute allocations in a sports fantasy league trade transaction. The computer implemented method includes, in one embodiment, calculating, based on an expected return associated with each player on each of a plurality of teams in a fantasy sports league, a valuation for each player. An embodiment includes determining a positional need for each of the plurality of teams in the fantasy sports league, and determining, based on the valuation for each player and the positional need for each team, one or more players to include in a trade with another team of the plurality of teams.