Now a days we hear biz words Natural Language Processing and Artificial Intelligence in our day to day life. Basically Natural Language Processing (NLP) refer Artificial Intelligence (AI) which allows computers to communicate with natural language human use.
Most of the clients from Healthcare, Finance, and Marketing etc. are moving towards to design and develop application which will help them to interact with their customers and provide quick response which involves answering questions posed by humans in a natural language.
Major thrust of AI is to build a machine that can understand commands written or spoken in natural Language. NLP is often used with artificial intelligence techniques designed to automate the learning process.
Common types/components of natural language processing are:
Application need to understand language to identify topics of given context to respond appropriately.
This includes below tasks:
- Spell checking
- Language modelling
This involves generating and formatting meaningful sentences and phrases in the form of natural language
Entity extraction involves identifying and extracting entities such as people, places, companies, etc. to simplify process. Understands the context of the supplied text, this includes adding explanation/comments for entities in given text depending on context.
This involves Semantic analyze to extract relevant and useful information from unstructured data and understand grammar. Tokenization helps to identify and process relevant elements in text and understand the topic discussed.
Sentiment analysis is used to understand customer sentiment about any decision/service in media. Most of us share our experience about any brand or any online purchase over the internet, based on this analyze data and figure out positive or negative comments. This helps many of the companies who provide services such as sell or buy products over the internet.