Natural Language processing is the type of programs that understand human speech as we speak. It is a part of Artificial Intelligence. It is the ability of a machine to understand and interpret human language the way it is written or spoken. The main aim of natural the language processing is that to make the computer as intelligent as a human being in understanding the language. The developer can perform a task such as sentiment analysis, speech recognition, and relationship extraction using natural language processing. You can still hire freelancers working on natural language processing.

Reasons for Studying Natural Language Processing:

  1. using this language computer communicate with users. The user does not have to learn a new language, and it is also useful to that user who does not have time to learn the new language.
  2. There is a bunch of information available on books, news paper, business, government paper, scientific paper and lot of information is available online. Using natural language processing, you can retrieve information that is available on your computer.
  3. Many of problems of Artificial Intelligence occur explicit and apparent from natural language processing it is the best domain that experiments with general theories.

Natural Language Generation:-

  • Text Planning: – From knowledge base, it retrieves the related content.
  • Sentence planning: – In Sentence planning chose the require words using that words form a meaningful sentence and setting the tone of a sentence.
  • Text Understanding: – It is the mapping of the sentence from sentence structure.

An aspect of Natural Language Understanding:

Syntax: – Syntax is the grammar structure and order of an element in a language statement. Syntax mostly describes the computer language and natural language. The natural grammar language is difficult than formal language that uses for artificial languages of logics and computer program.

Semantics: – Semantics tries to understand the meaning of language and how it is constructed by language as well as interpreted. Suppose if you create a natural language understanding system for the particular application you are trying to represent it simply.

Pragmatics: – The pragmatic is the study of linguistic signs, and words and sentences and it is also the study of human action and thought.  It is the most important key features to understanding the language.

Phonology: – Organising sound systematically.

Morphology: – construction of word from original, meaningful units.

Morpheme: – It is a prehistoric unit of meaning in language.

Discourse: -How interpretation sentence can affect the immediately preceding sentence.

World knowledge: – It gives knowledge regarding word.

Natural Language processing algorithm:

Natural language processing algorithm is based on machine learning algorithm. Natural language processing can depend on machine learning to automatically learn these rules by doing the analysis.

Automatically Generate Keyword tags which leverage LDA, a technique that discovers topics within the body of text. Summariser to extract the most important and central idea while ignoring irrelevant information. Using Parsley MCParseface create chatbot and language parsing deep learning mode. Using named entity recognition, it identifies the entity extracted from a person, place, and organization. Identify the sentiment of a string of text from negative to neutral to very positive using sentiment analysis. You can find freelancers working on this algorithm as well.

Application of Natural Language Processing:

  1. It is useful for grammar checking software and writing platform.
  2. Natural language converts better human-computer interfaces and vice versa. It is the best language for a visually impaired person to interact with computers. The interface to a database system in natural language processing which is useful for a travel agent for making the reservation.
  3. Natural language processing is a language that translates one human language to another human language. It is useful for rudimentary translation before the involvement of human translator. It reduces the time required for translating the document.
  4. The computer understands and process human language and converted into mass information from websites and before stocking into a huge database.
  5. Natural language convert has spoken the language into text. You can use deep learning technology to understand the human language.
  6. Using natural language processing sentiment analysis become easy it includes attitude, emotional state, and judgment or the intent of the writer.

Programming languages for Natural Language Processing:-

MATLAB:

MATLAB is excellent for representing and working with Matrices. MATLAB is a fourth generation programming language and platform to use when climbing into the linear algebra of given method. For technical computing, it is a high-performance language. It has easy to use environment. Using this language, you can perform Math computation, Algorithm development, scientific and engineering graphics. You can find freelancers who have Knowledge of MATLAB, and you also get certified freelancers for this language.

R:

R is a programming language used for statistical learning. It is language developed by John Chambers and colleagues. It is language that understands and explores your data using statistical methods and graphs. In natural language processing, R plays an important role in investigating big data, supporting researcher, and also useful for computationally intense learning analytics. It has an enormous number of natural language processing algorithms. Model and prototype with R is an excellent way.

Python:

A Python is a high-level object-oriented programming language, and it is simply easy to learn syntax readability and reduce the cost of maintenance. Python contains a lot of packages using this you can do code reusability. Natural language processing with Python can extract information from unstructured text, either to guess the topics and identity named entity. Using Python, Using parsing and semantic you can analyse language structure. Integrate systems drawn from various language and artificial intelligence. Python is an excellent language for natural language processing. It is scientific language and excellent for natural language processing.

Java:

Java has widely used programming language. It is the most popular programming language for Android Smartphone. Implement system using natural language processing is a challenging work. Natural language processing using Java will help you to explore how to automatically organize text using full-text search, clustering, tagging, and information extraction. Java is the best language for performing natural language processing because of its best features. It is a platform independent language because of this feature the processing of information becomes easy. You can hire freelancers who have complete knowledge of Java using natural language programming

Summary

In this article, you get information regarding what is natural language processing and its application in daily life. Why should study natural language? And the different aspect of natural language understanding. In last you get knowledge regarding different programming languages for developing Natural Language.

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