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What is Natural Language Processing (NLP)?

by Iwan Price-Evans on Artificial Intelligence • June 1, 2022

Natural language processing (NLP) is a field of computer science that uses natural language processing techniques to analyze text in order to extract information. NLP has applications in many fields, including search engines, speech recognition, machine translation, and artificial intelligence.

In its simplest form, natural language processing involves analyzing written or spoken words to determine what they mean. This process is often referred to as semantic analysis.

History of NLP

In the 1950s, researchers began using computers to analyze natural language. They were able to understand the meaning of sentences by analyzing the relationships between words. This was called “natural language understanding” (NLU). NLU became more sophisticated as computer technology improved. By the 1980s, NLU had advanced enough to allow computers to answer questions posed in natural language.

How Does NLP Work?

A computer program called a “natural language processor” analyzes text to identify key terms and phrases. These terms and phrases are then used to search databases containing relevant information. For example, when a user searches Google using the term “how do I…”, the natural language processor will analyze the query and use the results to find related web pages.

Types of NLP

There are two main categories of NLP: rule-based and statistical.

  • Rule-based systems use rules to determine what words mean and how they should be used.
  • Statistical methods rely on statistics to find patterns in text.

Examples of NLP

In addition to searching databases, natural language processors can also perform tasks such as summarizing documents, translating texts, and identifying patterns within data.