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Introduction to Natural Language Processing (NLP)

What is Natural Language Processing

Natural Language Processing (NLP). Is a technology that deals with the ability of computers to understand, interpret, and manipulate human language or commands. This technology enables computers to understand language through text and voice messages.

How Natural Language Processing Works

There are exactly 2 phases: data preprocessing and NLP algorithm development. In the cleaning phase,we clean the data by first removing unnecessary elements that interfere with NLP performance. We can divide the data cleaning stage into several processes.

  1. Tokenization: First steps to break down text into simpler steps
  2. Stop word removal: Second stage to remove hyphens
  3. Lemmatization and stemming:The third process of removing the conjunction, leaving only the original word, is essential.
  4. Part of speech tagging: This is the process of marking up writing according to its parts.

After passing the preprocessing or cleaning stage, the system will develop a new algorithm. This algorithm usually applies a rules-based system or machine learning-based system.

  1. Rules-based Linguists carefully design and develop comprehensive linguistic rules that systems use.
  2. Machine learning-based systems use statistical methods to modelling.

The Advantages and disadvantages of Natural Language Processing

Advantages

With such good capabilities, NLP has a variety of functions that can be used to help human daily work including

•   Process, analyze and archive large documents
•   Analyze customer feedback or call centre recordings
•   Running a chatbot for automated customer service

Disadvantages

•   The machine learning training process will take a very long time. Especially with large data and without a pretrain model.
•   Not 100% reliable, NLP isn’t 100% reliable due to potential errors, even in stable systems.

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