Recommending a dialog act using model-based textual analysis

A computer program product comprising one or more computer readable storage media, and program instructions collectively stored on the one or more computer readable storage media, the program instructions comprising instructions configured to cause one or more processors to perform a method comprising:

• receiving textual data associated with a conversation between a first participant and a second participant, utilizing the one or more processors;
• receiving an objective of the first participant for the conversation between the first participant and the second participant, utilizing the one or more processors, where the objective is separate from the conversation;
• determining, utilizing the one or more processors, a dialog act to be entered by the first participant that meets the objective, utilizing a machine learning model, the determining utilizing the machine learning model including:
• scoring a plurality of proposed dialog acts based on an amount that each proposed dialog act will change a probability of the objective being achieved during the conversation, and
• determining the dialog act to be entered, based on the scoring;
• and
• returning the determined dialog act to the first participant, utilizing the one or more processors.

A system, comprising:

• a processor;
• and
• logic integrated with the processor, executable by the processor, or integrated with and executable by the processor, the logic being configured to:
• receive, utilizing the processor, textual data associated with a conversation between a first participant and a second participant;
• receive, utilizing the processor, an objective of the first participant for the conversation between the first participant and the second participant, where the objective is separate from the conversation;
• determine, utilizing the processor, a dialog act to be entered by the first participant that meets the objective, utilizing a machine learning model, the determining utilizing the machine learning model including:
• scoring a plurality of proposed dialog acts based on an amount that each proposed dialog act will change a probability of the objective being achieved during the conversation, and
• determining the dialog act to be entered, based on the scoring;
• and return, utilizing the processor, the determined dialog act to the first participant.