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What is a rule-based chatbot?
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Summarized by durumis AI
- Rule-based chatbots are chatbots that operate according to pre-defined rules, providing predictable responses to user input.
- They are useful for FAQ chatbots, reservation systems, simple customer support services, and are easy to develop and maintain.
- However, they have drawbacks such as difficulty in responding to questions or situations not defined in the rules, limited scalability, and the need for ongoing maintenance.
A rule-based chatbot is a type of chatbot that operates based on predefined rules and logic. This system responds to user input according to a pre-defined set of rules, providing predictable responses to specific inputs. The core of a rule-based chatbot is the rule engine, which processes a set of rules defined by a series of conditions and actions, generating an appropriate response to the user's question or request.
What is 'rule-based' in chatbot?
Characteristics of Rule-Based Chatbots
Rule-Based System:
Rule-based chatbots operate using "IF-THEN" structured rules. For example, if a user enters "Hello," the chatbot is set up to respond with "Hello! How can I help you?".
Predefined Responses:
Since all responses are pre-defined, the chatbot always provides the same response to a specific question. This offers a consistent user experience but makes it difficult to handle complex or unexpected inquiries.
Use Cases:
Rule-based chatbots are mainly useful for answering simple questions or when standardized information delivery is required. They are often used in FAQ chatbots, reservation systems, simple customer support services, etc.
Ease of Implementation:
They are relatively easy to implement and do not require advanced natural language processing (NLP) techniques. This offers the advantage of low initial development costs and easy maintenance.
Advantages and Disadvantages of Rule-Based Chatbots
Advantages:
Predictability: All responses are pre-defined, so users can predict what kind of response they will receive.
Simple Implementation: They do not require complex machine learning models, making them quick and easy to implement.
Cost Efficiency: Development and maintenance costs are relatively low.
Disadvantages:
Lack of Flexibility: It is difficult to respond to questions or situations that are not defined in the rules.
Limited Scalability: Adding new rules can increase complexity, making management challenging in large-scale systems.
Continuous Maintenance Required: Rules need to be continuously updated and managed.
Examples of Rule-Based Chatbots
FAQ Chatbots:
Chatbots that provide answers to frequently asked questions. When a user asks a question like "How much is the shipping fee?", a list of pre-defined buttons appears, and clicking on a button provides the corresponding answer.
You can find answers by pressing the buttons under the defined rules
Customer Support Chatbots:
Chatbots that handle inquiries about specific products or services. For requests like "I want to file an AS request," they guide users through a step-by-step process with Q&A, ultimately transmitting the information to the existing AS management system.
This involves collecting the product category, symptoms, recipient's email address, phone number, and device location in a step-by-step manner and sending this information to the management system.