Natural language processing (NLP) analyzes and represents natural language text or speech at linguistic levels to achieve human-like language processing for applications. NLP was influenced by Turing's 1950 paper on machine intelligence and involved early systems like SHRDLU in the 1960s. NLP understands, generates, and integrates natural language through techniques like morphological, syntactic, semantic and discourse analysis to benefit domains like search, translation, sentiment analysis, social media and more.

1. Natural Language Processing
(NLP)
ASWIN KP
18390006
M.LIB.I.SC
PU

2. What is natural language processing?
• Process information contained in natural language text
• Also known as Computational Linguistics (CL), Human Language
Technology (HLT), Natural Language Engineering (NLE)

3. Definition
Natural Language Processing is a theoretically motivated range of
computational techniques for analysing and representing naturally
occurring texts/speech at one or more levels of linguistic analysis for
the purpose of achieving human-like language processing for a range of
tasks or applications

4. History
• In 1950, Alan Turing published an article titled "Machine and
Intelligence" which advertised what is now called the Turing test as a
subfield of intelligence
• Some beneficial and successful Natural language systems were developed
in the 1960s were SHRDLU, a natural language system working in restricted
"blocks of words" with restricted vocabularies was written between 1964
to 1966

5. Why NLP?
• A hallmark of human intelligence
• Text is the largest repository of human knowledge and is growing
quickly
• computer programmes that understood text or speech

6. Components of NLP
1 Natural Language Understanding
 Taking some spoken/typed sentence and working out what it means
 Mapping the given input in the natural language into a useful representation
 Different level of analysis required:
• morphological analysis
• syntactic analysis
• semantic analysis
• discourse analysis

7. 2 Natural Language Generation
Taking some formal representation of what you want to say and working
out a way to express it in a natural (human) language (e.g., English)
Producing output in the natural language from some internal
representation
 Different level of synthesis required
• deep planning (what to say)
• syntactic generation

8. Steps of NLP
Morphological and Lexical Analysis
Syntactic Analysis
 Semantic Analysis
 Discourse Integration
 Pragmatic Analysis

9. Future of NLP
➢Semantic Web/Search
➢Sentiment Analysis / Opinion Mining
➢Machine Translation
➢Advanced Speech Processing Application
➢Social Network Analysis
➢Collective Intelligence

10. NLP in other Domains
➢Bio-Medical
➢Forensic Science
➢Advertisement
➢Education
➢Politics
➢E-governance
➢Business Development
➢Marketing

11. Reference
• http://jaganadhg.freeflux.net/blog
• https://epgp.inflibnet.ac.in
• https://www.slideshare.net

12. THANKS