Human-machine dialogue method and electronic device

A human-machine dialogue method applicable to electronic devices, the method comprising:

• determining a set number of jump topics related to a specified field, and constructing a topic jump graph between the topics based on the correlation intensions among the set number of jump topics, wherein k path segments from each jump topic to k jump topics at a downstream level are configured respectively with an initial jump probability;
• determining a jump topic to which the user's dialogue request belongs as an initial topic for a first round of recommendation to the user after an initial response to a user's dialogue request;
• determining a jump topic for jumping to according to the jump probability of jumping out of the initial topic to the k jump topics at the downstream level for a next round of recommendation to the user after completing a human-machine dialogue of the initial topic;
• and
• continuing recommending the jump topics of the topic jump map for human-machine dialogue in a round-by-round recommendation manner.

An electronic device, comprising at least one processor and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, wherein execution of the instructions by the at least one processor causes the at least one processor to perform the steps of:

• determining a set number of jump topics around a target topic, and generating a topic jump map converging to the target topic based on the correlation intensions among the set number of jump topics, wherein k path segments from each jump topic to k jump topics at a downstream level are configured respectively with an initial jump probability;
• selecting from the topic jump map a jump topic to which the user's dialogue request belongs as an initial topic for a first round of recommendation to the user after an initial response to a user's dialogue request;
• determining a jump topic for jumping to according to the jump probability of jumping out of the initial topic to the k jump topics at the downstream level for a next round of recommendation to the user after completing a human-machine dialogue of the initial topic;
• and
• gradually guiding the dialogue from the initial topic to the target topic in a step-by-step recommendation manner.