Are NLUs expensive

What is the difference between NLP and NLU?

Many customers ask us in our chatbot projects: What is the difference between NLP and NLU? Which is better suited for developing good business chatbots in practice?

In this article you will learn the differences to NLP (Natural Language Processing) and NLU (Natural Language Understanding) and the advantages for business practice.

NLP and NLU, is there a difference?

In the field of artificial intelligence, there are various methods that a computer can use to examine text. Both NLP and NLU are used to understand natural language, i.e. human language. Often the terms are used synonymously. However, there are key differences between NLP and NLU. The methods differ in the type of words and sentences examined, as well as in the analysis and the hit rate.

What is NLP?

NLP is the acronym for “Natural language processing” and describes the processing of natural language information with the help of a computer. Specifically, this means that NLP enables free text input. This means that users can enter their concerns directly into the chatbot text window. The chatbot uses NLP technology to analyze the inputs and assign them to the previously trained intents. If the chatbot finds a suitable answer to the intent, it is output to the user.

The NLP chatbot searches a question for keywords and then gives the appropriate answer. In online shops - e-commerce is a chatbot area of ​​application - questions are often asked in which the words “price” or “cost” appear. An NLP chatbot will then likely provide a reference to a price list. A more sophisticated NLP chatbot also recognizes two keywords at the same time. This would make it possible to name the price of this product if the question "price" or "costs" and the name of a product appear.

NLP is therefore a quick and easy way of examining texts for their meaning with the help of software. The hit rate with the recognition of keywords is quite functional for simple questions. However, NLP reaches its limits as soon as the questions become too complicated or actual intentions are to be understood instead of individual keywords.

What is NLU?

NLU (Natural Language Understanding) is about understanding the meaning of a question or statement in detail. NLU works with the following rules:

  1. Correct identification of subject and object as well as any other expressions that may occur
  2. Correct recognition of the process or relation that a question is about
  3. If necessary, correct assignment of pronouns (if available)

Both semantic and context-sensitive pragmatic analyzes are used at NLU. With these techniques, the following sentence sequence, for example, can be answered correctly: "What kind of milk chocolate do you have? What do they cost? ”The chatbot recognizes that“ the ”on the“ whole milk chocolates ”results from the context and the keyword does not have to be used again. Even complex questions such as “Can I exchange the goods if they are already open?” Can be answered in this way. A "normal" chatbot that is "only" based on NLP has no chance with such questions.

NLU requirements include:

  • A comprehensive lexicon with different meanings of words (most words can have multiple meanings)
  • Detailed parsing of sentences (breaking down into its components)
  • Extensive context modeling

NLU enables deep semantic analysis

By combining a classic search engine and NLU, the chatbot improves search results by 40%. In the table you can see that NLU recognizes the text input: “My package is totally crushed”. A chatbot without NLU does not understand this natural parlance performance. This is why NLU is so important to a successful chatbot project.

Conclusion: As you can see in the article, the use of NLU has great advantages for companies, because natural language leads to better success in the output of correct search results. Kauz works with a specially developed NLU technology and uses this to achieve the best results for customer satisfaction. The result is that our chatbots can correctly understand and answer more questions almost every day.