Abstract: Input of a conversation is received. The conversation includes at least a first user. An utterance of the conversation is analyzed to identify a dialog act attribute, an emotion attribute, and a tone attribute. The dialog act attribute, emotion attribute, and tone attribute are annotated to the utterance of the conversation. The conversation is validated based on the annotated attributes compared with a threshold. The annotated conversation and the validation of the conversation are stored.

Abstract: A system, computer program product, and method are disclosed. In an approach to train customer service agent using chatbots. The method includes training a chatbot for a customer chat simulation based on a customer service conversation data, a task scenario, and a customer persona. The method also includes monitoring an interaction between a customer service agent and the chatbot. The method further includes determining an assessment of the performance of the customer service agent based on the interaction between the customer service agent and the chatbot. The method additionally includes generating feedback for the customer service agent based on the assessment of the performance of the customer service agent.

Abstract: A system, computer program product, and method are disclosed. In an approach to train customer service agent using chatbots. The method includes training a chatbot for a customer chat simulation based on a customer service conversation data, a task scenario, and a customer persona. The method also includes monitoring an interaction between a customer service agent and the chatbot. The method further includes determining an assessment of the performance of the customer service agent based on the interaction between the customer service agent and the chatbot. The method additionally includes generating feedback for the customer service agent based on the assessment of the performance of the customer service agent.

Abstract: Input of a conversation is received. The conversation includes at least a first user. An utterance of the conversation is analyzed to identify a dialog act attribute, an emotion attribute, and a tone attribute. The dialog act attribute, emotion attribute, and tone attribute are annotated to the utterance of the conversation. The conversation is validated based on the annotated attributes compared with a threshold. The annotated conversation and the validation of the conversation are stored.

Abstract: Input of a conversation is received. The conversation includes at least a first user. An utterance of the conversation is analyzed to identify a dialog act attribute, an emotion attribute, and a tone attribute. The dialog act attribute, emotion attribute, and tone attribute are annotated to the utterance of the conversation. The conversation is validated based on the annotated attributes compared with a threshold. The annotated conversation and the validation of the conversation are stored.

Abstract: Input of a conversation is received. The conversation includes at least a first user. An utterance of the conversation is analyzed to identify a dialog act attribute, an emotion attribute, and a tone attribute. The dialog act attribute, emotion attribute, and tone attribute are annotated to the utterance of the conversation. The conversation is validated based on the annotated attributes compared with a threshold. The annotated conversation and the validation of the conversation are stored.

Abstract: A computer program product for determining an impact of a proposed dialog act in a conversation according to one embodiment includes a computer readable storage medium having program instructions embodied therewith. The computer readable storage medium is not a transitory signal per se. The program instructions are executable by a processor to cause the processor to perform a method comprising receiving textual data associated with a real-time conversation between a first participant and a second participant, receiving an objective of the first participant for the real-time conversation between the first participant and the second participant, receiving a proposed dialog act to be entered at a current point in the real-time conversation from the first participant, determining an impact of the proposed dialog act on the objective of the first participant, and performing one or more actions based on the impact of the proposed dialog act.

Abstract: A method, a computer program product, and an information handling system is provided for labeling unlabeled utterances given a taxonomy of labels utilizing topic word semi-supervised learning.

Abstract: A computer program product for recommending a dialog act to a participant in a conversation according to one embodiment includes a computer readable storage medium having program instructions embodied therewith. The computer readable storage medium is not a transitory signal per se, where the program instructions are executable by a processor to cause the processor to perform a method including receiving textual data associated with a real-time conversation between a first participant and a second participant, utilizing the processor, receiving an objective of the first participant for the real-time conversation between the first participant and the second participant, utilizing the processor, determining, utilizing the processor, a dialog act to be entered by the first participant at a current point in the real-time conversation that meets the objective, utilizing a model, and returning the dialog act to the first participant, utilizing the processor.

Abstract: A computer program product for determining an impact of a proposed dialog act in a conversation according to one embodiment includes a computer readable storage medium having program instructions embodied therewith. The computer readable storage medium is not a transitory signal per se. The program instructions are executable by a processor to cause the processor to perform a method comprising receiving textual data associated with a real-time conversation between a first participant and a second participant, receiving an objective of the first participant for the real-time conversation between the first participant and the second participant, receiving a proposed dialog act to be entered at a current point in the real-time conversation from the first participant, determining an impact of the proposed dialog act on the objective of the first participant, and performing one or more actions based on the impact of the proposed dialog act.

Abstract: A computer-implemented method according to one embodiment includes receiving, utilizing a processor, textual data associated with a real-time conversation between a first participant and a second participant, receiving, utilizing the processor, an objective of the first participant for the real-time conversation between the first participant and the second participant, receiving, utilizing the processor, a proposed dialog act to be entered at a current point in the real-time conversation from the first participant, determining, utilizing the processor, an impact of the proposed dialog act on the objective of the first participant, utilizing a model, and performing, utilizing the processor, one or more actions based on the impact of the proposed dialog act.

Abstract: A computer-implemented method according to one embodiment includes receiving, utilizing a processor, textual data associated with a real-time conversation between a first participant and a second participant, receiving, utilizing the processor, an objective of the first participant for the real-time conversation between the first participant and the second participant, determining, utilizing the processor, a dialog act to be entered by the first participant at a current point in the real-time conversation that meets the objective, utilizing a model, and returning, utilizing the processor, the dialog act to the first participant.

Abstract: An approach is provided that provides a communication tone coach. The approach may obtain communication information regarding a communication between a first entity and a second entity while the communication may be ongoing. The communication may include an utterance. A tone associated with the utterance may be identified and may result in an identified tone. An outcome of the communication may be predicted using a machine learning based prediction module and the identified tone.

Abstract: An approach is provided that provides a communication tone coach. The approach may obtain communication information regarding a communication between a first entity and a second entity while the communication may be ongoing. The communication may include an utterance. A tone associated with the utterance may be identified and may result in an identified tone. An outcome of the communication may be predicted using a machine learning based prediction module and the identified tone.

Abstract: Input of a conversation is received. The conversation includes at least a first user. An utterance of the conversation is analyzed to identify a dialog act attribute, an emotion attribute, and a tone attribute. The dialog act attribute, emotion attribute, and tone attribute are annotated to the utterance of the conversation. The conversation is validated based on the annotated attributes compared with a threshold. The annotated conversation and the validation of the conversation are stored.

Abstract: An approach is provided that uses an availability of a computer resource to tailor an assistance with a task. An adaptive cognitive agent obtains a task assignment. The adaptive cognitive agent obtains an availability of a computer resource available to the adaptive cognitive agent. The availability of the computer resource is used to tailor an assistance with the task, resulting in an assistance plan being stored in a memory.

Abstract: An approach is provided that provides a tone optimization recommendation. The approach obtains a current tone inferred from digital content and a desired tone inference for a target audience. A tone optimization recommendation to reduce a difference between the current tone and the desired tone is determined using a processor. A memory is modified to save the tone optimization recommendation. The tone optimization recommendation is provided.

Abstract: A method, system and a computer program product are provided for making product recommendations to improve a user's personal brand by using the symbolic meanings and utilities of products and a user's brand perceptions along with users input of a desired personal brand imagery to output a set of products that are optimized to help users bridge the gaps between their desired and actual self-brand, thereby enabling a user to navigate products that shape their personal imagery.

Abstract: A method, system and a computer program product are provided for enabling personal branding by using the symbolic meanings and utilities of products and a user's brand perceptions along with users input of a desired personal brand imagery to output visual information identifying one or more gaps between the user's desired and actual self-brand, thereby enabling a user to navigate products that shape their personal imagery.

Abstract: A mechanism is provided in a data processing system comprising at least one processor and at least one memory, the at least one memory comprising instructions executed by the at least one processor to cause the at least one processor to implement a personalized interactive decision support system. A customer profile generator executing within the personalized interactive decision support system determines a set of traits for at least one customer based on at least one user-generated content source. A personalized product recommendation module executing within the personalized interactive decision support system matches the at least one customer to at least one product within a set of products based on a consumption preferences-to-product attribute mapping data structure to form at least one product recommendation.