Natural Language Processing – Overview
- Natural language processing (NLP) is the interactions between computers and human language, how to program computers to process and analyse large amounts of natural language data.
- The technology can accurately extract information and insights contained in the documents as well as categorize and organize the documents themselves.
- NLP makes computers capable of “understanding” the contents of documents, including the contextual nuances of the language within them.
- Most higher-level NLP applications involve aspects that emulate intelligent behavior and apparent comprehension of natural language.
- Many different classes of machine-learning algorithms have been applied to natural-language-processing tasks.
- These algorithms take as input a large set of “features” that are generated from the input data.
Natural Language Processing – Market Size
Natural Language Processing Market was valued at USD 11.02 Billion in 2020 and is projected to reach USD 45.79 Billion by 2028, growing at a CAGR of 19.49 % from 2021 to 2028.
Natural Language Processing – Segmentation Analysis
Natural Language Processing – Advantages
- Better data analysis
- Streamlined processes
- Empowered employees
- Enhanced customer experience
Natural Language Processing – 5 Phases
- Phase 1 – Lexical Analysis
- Phase 2 – Syntactic Analysis
- Phase 3 – Sematic Analysis
- Phase 4 – Discourse Analysis
- Phase 5 – Pragmatic Analysis
Phase 1 – Lexical Analysis
- Lexical analysis is the process of converting a sequence of characters into a sequence of tokens.
- A lexer is generally combined with a parser, which together analyzes the syntax of programming languages, web pages, and so forth.
- Lexers and parsers are most often used for compilers but can be used for other computer language tools, such as pretty printers or linters.
- Lexical analysis is also an important analysis during the early stage of natural language processing, where text or sound waves are segmented into words and other units.
Phase 2 – Syntactic Analysis
- Parsing, syntax analysis, or syntactic analysis is the process of analyzing a string of symbols, either in natural language, computer languages, or data structures, conforming to the rules of formal grammar.
- It is used in the analysis of computer languages, referring to the syntactic analysis of the input code into its component parts to facilitate the writing of compilers and interpreters.
- Grammatical rules are applied to categories and groups of words, not individual words. The syntactic analysis basically assigns a semantic structure to text.
- Syntactic analysis is a very important part of NLP that helps in understanding the grammatical meaning of any sentence.
Phase 3 – Semantic Analysis
- Semantic Analysis attempts to understand the meaning of Natural Language.
- Semantic Analysis of Natural Language captures the meaning of the given text while considering context, logical structuring of sentences, and grammar roles.
- 2 parts of Semantic Analysis are (a) Lexical Semantic Analysis and (b) Compositional Semantics Analysis.
- Semantic analysis can begin with the relationship between individual words.
Phase 4 – Discourse Analysis
- Researchers use Discourse analysis to uncover the motivation behind a text.
- It is useful for studying the underlying meaning of a spoken or written text as it considers the social and historical contexts.
- Discourse analysis is a process of performing text or language analysis, involving text interpretation, and understanding the social interactions.
Phase 5 – Pragmatic Analysis
- Pragmatic Analysis is part of the process of extracting information from text.
- It focuses on taking a structured set of text and figuring out the actual meaning of the text.
- It also focuses on the meaning of the words of the time and context.
- Effects on interpretation can be measured using PA by understanding the communicative and social content.