NLP in-depth overview

NLP is the art of analyzing and understanding human languages by machines. According to many studies, more than 75% of the used data is unstructured. Unstructured data does not have a predefined data model or not organized in a predefined manner. Emails, tweets, daily messages and even our recorded speeches are forms of unstructured data. NLP is a way for machines to analyze, understand, and derive meaning from natural language. NLP is widely used in many fields and applications, such as:

• Real-time translation
• Automatic summarization
• Sentiment analysis
• Speech recognition
• Build chatbots

Generally, there are two different components of NLP:

• Natural Language Understanding (NLU): This refers to mapping input into a useful representation.
• Natural Language Generation (NLG): This refers to transforming internal representations into useful representations. In other words, it is transforming data into written or spoken narrative. Written analysis for business intelligence dashboards is one of NLG applications.

Every NLP project goes through five steps. To build an NLP project the first step is identifying and analyzing the structure of words. This step involves piding the data into paragraphs, sentences, and words. Later we analyze the words in the sentences and relationships among them. The third step involves checking the text for  meaningfulness. Then, analyzing the meaning of consecutive sentences. Finally, we finish the project by the pragmatic analysis.