Rule-based chatbots and chatbots based on NLP technology. A substantial difference.

Burduja Irina
Extremesetup
Published in
3 min readJul 28, 2019

The theme of chatbots is very popular and highly discussed present-day. It is interesting but at the same time challenging course that modern technology takes. Nevertheless, it remains still an intrigue which level this technology will reach until the end.
In order to bring to mind what a chatbot really is and which services it is ready to provide us, it is meant to point out that this is nothing else than a computer program which is developed particularly to interact over the internet, but not only, with human users. These smart-systems are able to imitate a real conversation that will be indistinguishable from that of human to human one.
For all that, it is necessary to take into consideration that there is a considerable variety of chatbots. While some of them are very primitive, being able to go just through some simple and elementary tasks, and doing their job really well when it is needed, the others are surprisingly advanced being ahead in position, time and manner. These artificial clever interlocutors are required there where we are talking about more complicated schemes and more sophisticated assignments.
That is why it is more than necessary to know how to discover the right variant of a chatbot for certain needs.
There are two main categories of chatbots that we can distinguish.
1. Rule-based chatbots. The principle of powering such type of chatbots is a very simple one. These computer systems are trained to answer a certain amount of questions and to solve a certain amount of problems through a series of well-defined rules. The rules could have a large diapason of complicity, from diminishing to medium and elevated.
Talking about rule-based chatbots we need to consider the following circumstances:
• A rule-based bot will answer only those question for which it was prepared. We must take into account that the developers are writing certain rules for a certain scenario. Accordingly, a scenario that will be out of it — will not work.
• The process of writing rules in order to create a rule-based chatbot demands a lot of time. Besides, it is absolutely impossible to write rules for all possible scenarios in order to cover all needs. That is why such types of chatbots have clear limits.
• The rule-based chatbots and Turing Test. A rule-based chatbot will never be able to pass the Turing Test. Because of their origin of creation, these computer systems are not capable of thinking like a human being, they just are following the “if-then” scheme.
2. Chatbots based on NLP technology. Here is the moment where starts the “delicious” part. These chatbots are developed in such a way, that they are capable of picking up the meaning from the input given by users because Natural Language Processing is based on deep learning. Correspondingly to a human being, an NLP based chatbot will generate an answer which will be based on contextual analysis. Such a smart chatbot will become even smarter with every interaction and conversation in which it will be involved. As a result, the number of problems that it will be able to solve will be on the growing hand considerably and constantly.
Hereinafter, let us specify those benefits that a leading NLP Based chatbot result in:
• An NLP Based chatbot is much more efficient than a rule-based one. Therefore, it is able to cover a much wider range of tasks.
• It learns fast. Every conversation makes them more and more intelligent.
• It gives inclusive answers. Using an understandable language, it makes it easy for the user to communicate, and get the help wanted.
Using a chatbot that is NLP-based, the human on the other side will have that certain feeling of having a true conversation but not just going through some boring software menus.
In order to make a short generalization, it is important to acknowledge that chatbots are our highly needful assistants. Be it a simple one, i.e. a rule-based chatbot, or a more sophisticated model like powered with artificial intelligence, the key is to know how to choose the perfect conversational agent for a certain charge.

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