Natural Language Processing is a subset branch of Artificial Intelligence that enables or pushes the capability of a machine to understand, interpret human languages which help to analyze emotions, actions, and thoughts. Natural Language Processing also helps to analyze data and extract information that may be needed to produce meaningful service or serve needs for a project.
We use Natural Language Processing or NLP in short in our daily life. Some of us even use it while writing some great article content, let's understand further:
- Chatbots - Chatbots are a great example of Natural Language Processing, where it uses NLP and Machine Learning algorithms to understand and reply as best possible to the user.
- Text Analysis - Text Analysis is one of the applications of Natural Language Processing, where it enables us to get insights into the text and helps to abstract the various insights of the text, including morphological or grammatical analysis.
- Sentiment Analysis - Sentiment analysis which is a subset of Social medial monitoring, Natural Language Analysis plays a huge role in analyzing the emotion of the sentence.
- Spell Check - One of the applications of NLP is the ability of Spell Check which we use in our daily life to make sure about the authenticity of any article or text blog.
- Email Classification - During the classification of email, Natural Language Processing helps to differentiate among emails to make sure that the user gets the best experience from the service.
Components of Natural Language Processing
Natural Language Processing has two Components, namely:
- Natural Language Generation (NLG)
- Natural Language Understanding (NLU)
Natural Language Generation - Natural Language Generation or NLG, in short, can be defined as the process of processing meaningful phrases and sentences in the form of Natural Language. It mainly involves:
- Text Realization
- Text Planning
- Sentence Planning
Natural Language Understanding - Natural Langauge Understanding or NLU, in short, can be defined as mapping the given input in Natural Language into some useful representation, by analyzing different aspects of the language.
General Steps in Natural Language Processing
Generally in Natural Language Processing, the process consists of five steps:
- Lexical Analysis
- Syntactic Analysis
- Semantic Analysis
- Discourse Integration
- Pragmatic Analysis
Lexical Analysis
It may be defined as identifying and analyzing the structure of words. It is breaking the whole chunk of the text into the required phrases.
Syntactic Analysis
Syntactic Analysis involves the process of analysis of words and generating words in the sentence following relation manner or following rules of grammar.
Semantic Analysis
Semantic Analysis is the drawing of the exact meaning or the dictionary meaning from the text provided, provided meaningfulness, usually done by mapping structures.
Discourse Integration
It is the process of bringing the sentence a meaning immediately after processing or succeeding sentence.
Pragmatic Analysis
Reinterpreted the actual meaning of the sentence.
OpenSource for NLP
Some of the libraries that provide building blocks of NLP in real-world applications are:
MALLET
It is an integrated collection of Java Code. Primarily used for Natural Language Processing, Cluster Analysis, Information Extraction, Machine Learning application to text.
Apache OpenNLP
It is one of the toolkits for the processing used in Natural Language Processing, supports the most common task in NLP, like parsing, language detection, conference resolution name entity extraction, sentence segmentation, etc.
Natural Language Toolkit (NLTK)
It is built for Python Programs to support Natural Langauge Processing. NLTK is a wonderful tool for teaching, working in Computational linguistic in Python.
Conclusion
It's great to see and understand how Natural Langauge processing is enabling technology to serve humankind and to empower more services. As we are using more technology, technology is serving to the potential. NLP will be empowering more in the near future and we can expect many more applications.