Different types of chatbots: Rule-based vs. NLP

Editor's note: This blog post was originally written on the Flow.ai website. Flow.ai was acquired by Khoros in 2021 to advance Khoros' conversational AI and machine learning (ML) capabilities and data science expertise. This blog post has been adapted to be on the Khoros blog.

Chatbots are relatively new and the rise of artificial intelligence is introducing many new developments. Chatbots are one of the first examples where AI can be applied in practice. The behavior of bots where AI is applied differs enormously from the behavior of bots where this is not applied.

In this article, we’ll tell you more about the rule-based chatbot and the NLP (Natural Language Processing) chatbot.

Rule-based bots

With this type of bot, communication is through pre-set rules. User input must conform to these pre-defined rules in order to get an answer. Often with such bots only buttons are used.

Since no artificial intelligence is used here, an open conversation with this type of bot is not possible or very limited.

NLP of AI Bots

Artificial Intelligence (AI) is still an unclear concept for many people. The idea behind this is to make robots “think like humans”. That includes many aspects and that is why it is such a broad concept. You can think of features such as logical reasoning, planning and understanding languages.

Understanding languages is especially useful when it comes to chatbots. Unlike the rule-based bots, these bots use algorithms (neural networks) to process natural language. This is where the term NLP or Natural Language Processing comes from.

NLP chatbots learn languages in a similar way that children learn a language. After having learned a number of examples, they are able to make connections between questions that are asked in different ways.

In this way, the bot understands what the question is about without being precisely programmed for it and an appropriate answer can be given. In a conversation form, this is also called Conversational AI.