쨋봇(챗봇) 에 관하여 가장 기본적이면서 개념적인 설명

Chatbots, the intelligent virtual assistants that simulate human conversations, can be classified based on how they generate responses, their range of conversation topics, and their ability to take initiative in a conversation.

The rule-based model is the simplest approach, where responses are predefined and triggered by a series of rules or decision trees. Retrieval-based models use machine learning algorithms to select responses from existing dialogues, improving their selection over time. Generative chatbots use deep learning to formulate original responses based on user input, but they require large amounts of data and are more prone to errors.

Chatbots can also be classified based on their conversation domains. Closed domain chatbots have a specific focus, like booking a hotel room, while open domain chatbots can cover any range of conversation topics, like a friend or therapist. Open domain chatbots are more challenging to implement and evaluate but have greater potential for emotional connection.

Finally, chatbots can be classified based on who takes the initiative in the conversation. A mixed-initiative system allows both the user and bot to take control, while a system-initiative system places the chatbot in control of the conversation. The latter is simpler to implement but lacks the flexibility and naturalness of a normal human dialogue.