Abstract: An approach is provided for generating a response by a cognitive entity. A question input by a user to the cognitive entity is received. A context of the user is determined. Based on the context of the user, an amount of detail for the response to the question is selected from different amounts of detail. The response is generated and presented to the user so that the response has the selected amount of detail.

Abstract: A model-based approach for transforming data. A modeling framework that includes a plurality of rules for performing transformations of data is developed. A data unit is configured. The data unit is assigned to a job that includes one or more rules of the plurality of rules. The job transforms the data unit from a data format of a source system into a data format of a destination system. Usage statistics for at least one rule of the job are monitored. An aggregate rule is determined based on a first atomic rule and a second atomic rule. The first atomic rule and the second atomic rule are identified by at least one, or in part by a common pattern. A first rule of the job is identified based on the usage statistics of a plurality of data units. The first rule is removed from memory.

Abstract: To guide a conversation based on cognitive analytics, data of the conversation up to a time in the conversation is received from a conversation interface while the conversation is continuing. Current data is received from a data source. The current data relates to a remote participant in the conversation and a topic in the conversation. A sentiment value of the remote participant during the conversation is determined from the current data and the conversation data. While the conversation is continuing, data of a prompt is introduced into the conversation. The data of the prompt is configured to cause the conversation to increase the sentiment value of the remote participant. A profile of the remote participant is updated with the sentiment value, to form an updated profile. The updated profile is used as a second data source in a later portion of the conversation.

Abstract: To guide a conversation based on cognitive analytics, data of the conversation up to a time in the conversation is received from a conversation interface while the conversation is continuing. Current data is received from a data source. The current data relates to a remote participant in the conversation and a topic in the conversation. A sentiment value of the remote participant during the conversation is determined from the current data and the conversation data. While the conversation is continuing, data of a prompt is introduced into the conversation. The data of the prompt is configured to cause the conversation to increase the sentiment value of the remote participant. A profile of the remote participant is updated with the sentiment value, to form an updated profile. The updated profile is used as a second data source in a later portion of the conversation.

Abstract: A model-based approach for transforming data. A modeling framework that includes a plurality of rules for performing transformations of data is developed. A data unit is configured. The data unit is assigned to a job that includes one or more rules of the plurality of rules. The job transforms the data unit from a data format of a source system into a data format of a destination system. Usage statistics for at least one rule of the job are monitored. An aggregate rule is determined based on a first atomic rule and a second atomic rule. The first atomic rule and the second atomic rule are identified by at least one, or in part by a common pattern. A first rule of the job is identified based on the usage statistics of a plurality of data units. The first rule is removed from memory.