1, knowledge base construction
Knowledge base construction is the foundation of intelligent customer service robot. The more information stored in the knowledge base, the wider the knowledge involved, the richer the questions that the intelligent customer service robot can answer, and the more effective it is to solve customer problems. So, where does the information in the knowledge base come from? This requires enterprises to import industry knowledge and related question and answer information, or obtain other information through external interfaces.
2. Semantic understanding
Intelligent customer service robot uses natural language processing technology and deep network neural algorithm model to understand the user's meaning and the true meaning expressed by the sentence through the structure and content of the whole sentence. Semantic understanding is like the "brain" of an intelligent customer service robot. It can be said that the understanding ability directly determines the intelligence of the intelligent customer service robot.
3. Question and answer matching
When the intelligent customer service robot understands the customer's questions through semantics, it will compare them in the knowledge base according to the understanding and choose the most matching questions and answers. Under normal circumstances, there will be no problems with the answers given, and customers can understand them.
4. Deep learning
Intelligent customer service robots can learn from a large number of unlabeled data, automatically summarize language rules from the data, handle complex language changes, and model complex emotions. As time goes by, intelligent customer service robots will become more and more powerful and intelligent.