Graph based prediction for next action in conversation flow

A computer program product for predicting a next action in a conversation system, the computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to:

• obtain, by the processor, information from conversation logs and a conversation design;
• create, by the processor, a dialog graph based on the conversation design;
• determine, by the processor, weights for edges in the dialog graph based on the information from the conversation logs and adding user input and external context information to an edge attributes set;
• analyze, by the processor, an unrecognized user input and predicting a next action based on dialog nodes in the dialog graph and historical paths;
• generate, by the processor, a guiding conversation response based on the predicted next action;
• improve, by the processor, the conversation design upon non-acceptance of the guiding conversation response based on analyzing the historical records including exception records, issue records and prediction results;
• and
• update, by the processor, dialog nodes and conversation transition logics based on historical records.

An apparatus comprising:

• a memory configured to store instructions;
• and
• a processor configured to execute the instructions to:
• obtain information from conversation logs and a conversation design;
• create a dialog graph based on the conversation design;
• determine weights for edges in the dialog graph based on the information from the conversation logs and adding user input and external context information to an edge attributes set;
• analyze an unrecognized user input and predict a next action based on dialog nodes in the dialog graph and historical paths;
• generate a guiding conversation response based on the predicted next action;
• improve the conversation design upon non-acceptance of the guiding conversation response based on analyzing the historical records including exception records, issue records and prediction results;
• and
• update dialog nodes and conversation transition logics based on historical records.