Abstract: A plurality of best practice rules pertaining to best practices for interacting with a system can be received. A first user interaction from a user can received. A best practice determiner can determine whether the first user interaction fits at least one of the best practice rules. Responsive to determining, by the best practice determiner, that the first user interaction does not fit the at least one of the best practice rules, a modified user interaction can be generated by modifying the first user interaction based, at least in part, on the received plurality of best practice rules. The modified user interaction can be presented to the user.

Abstract: In an approach to improve prompt variations to enhance user-based experiences while interacting with artificial intelligent (AI) systems, embodiments generate variations of the prompts associated with the initial input by automatically leveraging machine learning techniques and collect the prompts from a user resulting from an interaction with an artificial intelligent (AI) system. Further, embodiments, identify a heuristic to organize suggestions and the variations of the prompts, and determine and utilize the heuristic to organize the variations of the prompts in systematic categories to produce an efficient display of the variations of the prompts, in a graphic user interface (GUI), for the user to view. Additionally, embodiments, update the variations of the prompts based on identified interaction data from the user, and dynamically output the updated variations of the prompts in response to the identified and collected user data.

Abstract: Provided are techniques for moderating Artificial Intelligence (AI) agent interlocution in group dialog environments. Under control of an interlocution module that has been trained with dialog content and dialog turns, an indication that interlocution is to be determined for a group dialog is received. Under control of the interlocution module, it is determined whether an AI agent is to participate in the group dialog based on a current dialog context and a dialog response. Under control of the interlocution module, in response to determining that the AI agent is to participate in the group dialog, the AI agent is triggered to post the dialog response to the group dialog.

Abstract: Embodiments are provided that related to a computer system, a computer program product, and a computer-implemented method for dynamically managing knowledge graphs and their corresponding datasets. Embodiments include identifying a neologism from a virtual environment, and leveraging a virtual environment exploration to resolve a meaning of the identified neologism. The resolved meaning of the neologism is applied to a dynamic expansion of a dataset and a corresponding knowledge graph.

Abstract: A plurality of best practice rules pertaining to best practices for interacting with a system can be received. A first user interaction from a user can received. A best practice determiner can determine whether the first user interaction fits at least one of the best practice rules. Responsive to determining, by the best practice determiner, that the first user interaction does not fit the at least one of the best practice rules, a modified user interaction can be generated by modifying the first user interaction based, at least in part, on the received plurality of best practice rules. The modified user interaction can be presented to the user.

Abstract: In an approach to improve prompt variations to enhance user-based experiences while interacting with artificial intelligent (AI) systems, embodiments generate variations of the prompts associated with the initial input by automatically leveraging machine learning techniques and collect the prompts from a user resulting from an interaction with an artificial intelligent (AI) system. Further, embodiments, identify a heuristic to organize suggestions and the variations of the prompts, and determine and utilize the heuristic to organize the variations of the prompts in systematic categories to produce an efficient display of the variations of the prompts, in a graphic user interface (GUI), for the user to view. Additionally, embodiments, update the variations of the prompts based on identified interaction data from the user, and dynamically output the updated variations of the prompts in response to the identified and collected user data.

Abstract: Provided are techniques for moderating Artificial Intelligence (AI) agent interlocution in group dialog environments. Under control of an interlocution module that has been trained with dialog content and dialog turns, an indication that interlocution is to be determined for a group dialog is received. Under control of the interlocution module, it is determined whether an AI agent is to participate in the group dialog based on a current dialog context and a dialog response. Under control of the interlocution module, in response to determining that the AI agent is to participate in the group dialog, the AI agent is triggered to post the dialog response to the group dialog.

Abstract: A present invention embodiment analyzes user input via natural language processing. A natural language utterance from a user is analyzed to determine one or more computing tasks. the natural language utterance is analyzed using a knowledge base to identify one or more modifications to the natural language utterance that are based on previous user modifications to a previous user utterance. An indication that the user accepted at least one modification of the one or more modifications is received, wherein the at least one modification modifies the one or more computing tasks. The modified one or more computing tasks are executed.

Abstract: A method, computer system, and a computer program product for data labeling is provided. The present invention may include receiving a plurality of labeled data points. The present invention may include identifying one or more of the plurality of labeled data points with conflicting labels. The present invention may include determining that at least one of the one or more identified labeled data points exceeds one or more conflict thresholds. The present invention may include presenting the at least one or more identified labeled data points exceeding one or more conflict thresholds to a user. The present invention may include receiving a conflict resolution from the user for the one or more identified labeled data points exceeding the one or more conflict thresholds.

Abstract: Embodiments are provided that related to a computer system, a computer program product, and a computer-implemented method for dynamically managing knowledge graphs and their corresponding datasets. Embodiments include identifying a neologism from a virtual environment, and leveraging a virtual environment exploration to resolve a meaning of the identified neologism. The resolved meaning of the neologism is applied to a dynamic expansion of a dataset and a corresponding knowledge graph.

Abstract: Crowdsourced solutions are provided that can prevent and/or reduce dissemination of selected digital content in a social media platform. In one embodiment, a system can include at least one memory device having computer-executable components stored therein, and at least one processor configured to execute the computer-executable components. Such computer-executable components can include a selection component that identifies multiple reviewer accounts using a selection criterion corresponding to a user account in the social media platform. The multiple reviewer accounts can evaluate presence of particular digital content in the social media platform directed to the user account. The computer-executable components also can include a routing component that can provide portions of digital content directed to the user account to respective reviewer accounts.

Abstract: A reminder method, system, and computer program product include collecting information and an activity of a user, determining an optimum time to send the reminder to the user based on the information and the activity of the user and an optimal platform to deliver the reminder to the user based on the information and the activity of the user.

Abstract: A cognitive request management method, system, and computer program product include scanning a stream of incoming messages among at least two users to identify a request sent to a first user, storing the identified request in a list of unfulfilled requests, identifying a response of the first user to the request by backtracking within a message thread of the stream of incoming messages and when the response to a request is detected, the request is moved from the user's unfulfilled request list to a list of fulfilled requests, and displaying the list of unfulfilled requests and the list of fulfilled requests.

Abstract: Crowdsourced solutions are provided that can prevent and/or reduce dissemination of selected digital content in a social media platform. In one embodiment, a system can include at least one memory device having computer-executable components stored therein, and at least one processor configured to execute the computer-executable components. Such computer-executable components can include a selection component that identifies multiple reviewer accounts using a selection criterion corresponding to a user account in the social media platform. The multiple reviewer accounts can evaluate presence of particular digital content in the social media platform directed to the user account. The computer-executable components also can include a routing component that can provide portions of digital content directed to the user account to respective reviewer accounts.

Abstract: A reminder method, system, and computer program product include collecting information and an activity of a user, determining an optimum time to send the reminder to the user based on the information and the activity of the user and an optimal platform to deliver the reminder to the user based on the information and the activity of the user.

Abstract: A reminder method, system, and computer program product include collecting information and an activity of a user, determining an optimum time to send the reminder to the user based on the information and the activity of the user and an optimal platform to deliver the reminder to the user based on the information and the activity of the user.

Abstract: Embodiments of the present invention address deficiencies of the art in respect to context sensitive resource recommendations and provide a method, system and computer program product for activity sensitive context sensitive resource recommendations. In an embodiment of the invention, an activity-centric resource recommendation method can be provided. The method can include inferring an activity from a workspace in a graphical user interface, identifying resources from amongst a set of resources that are relevant to the inferred activity, and displaying the identified resources in the graphical user interface.

Abstract: A reminder method, system, and computer program product include collecting information and an activity of a user, determining an optimum time to send the reminder to the user based on the information and the activity of the user and an optimal platform to deliver the reminder to the user based on the information and the activity of the user.

Abstract: A cognitive request management method, system, and computer program product include scanning a stream of incoming messages among at least two users to identify a request sent to a first user, storing the identified request in a list of unfulfilled requests, identifying a response of the first user to the request by backtracking within a message thread of the stream of incoming messages and when the response to a request is detected, the request is moved from the user's unfulfilled request list to a list of fulfilled requests, and displaying the list of unfulfilled requests and the list of fulfilled requests.

Abstract: Embodiments are directed to an image processing station for associating a non-trusted data set with a trusted data set. The station includes a memory and a user interface configured to receive the trusted data set and the non-trusted data set. The station further includes a processor system communicatively coupled to the memory and the user interface. The processor system is configured to generate, based at least in part on processing the trusted data set and the non-trusted data set, a confidence value that represents a probability that at least a portion of the non-trusted data set identifies at least a portion of the trusted data set.