This document summarizes a seminar review on natural language processing. It defines NLP as using AI to communicate with intelligent systems in a human language like English. It outlines the steps of defining representations, parsing information, and constructing data structures. It also lists some of the basic components, applications, implementations, algorithms, and companies involved in NLP.

1. Seminar Review.
Natural Language
Processing.
Jayneel Vora, 15BCE048.

2. Introduction
● Ability for computers to
interpret natural human speech
and writing patterns.

3. Natural
Language.
● Natural Language Processing (NLP) refers to
AI method of communicating with an
intelligent systems using a natural language
such as English.
● Processing of Natural Language is required
when you want an intelligent system like
robot to perform as per your instructions,
when you want to hear decision from a
dialogue based clinical expert system, etc.

4. Steps.
● defining representations of information
● parsing that information from the data generating process
● constructing, storing, and using data structures that store information
Difficulties.
● the rules governing the representation of information in natural languages evolved
without predetermination.
Set of Rules:
1. High Level: Sarcasm
2. Low Level: add ‘s’ for plural form.

5. Components
Of
NLP.
● Natural Language
Understanding
● Natural Language Generation

6. Basic
Terminology
● Phonology
● Morphology
● Morpheme
● Syntax
● Semantics
● Pragmatics
● Discourse
● World Knowledge

7. Application 1 Keyword Matching.

8. Application 2 Machine Translation.

9. Application 3 Dialog Systems.
Psychiatrist Help for Emotional Help.

10. Application 4 Sentimental Analysis.

11. Application 5 Text Classification.

12. Application 6 Question Answering

13. Application 7 Advanced Search!

14. Information Extraction.

15. Implementations.
● NLTk-Sentiment analysis.
Also using VADER.

16. Implementations.
Textblob.
Tagging, Sentiment Analysis.

17. Implementations.
Textblob.
Tokenization, Lemmatization.

18. Implementations.
Textblob.
Spelling Correction
Language Detection and
Translation.

19. Implementations.
FeedParser.
RSS Feed readers.

20. Algorithms
Involved.
TextRank
Rank Sink
Page Rank

21. Companies
involved.
Expect Labs-Voice Recognition
SwiftKey-Text Prediction
NetBase-Social Media Anlaysis
FiscalNote- Goverment
Legislation
Klevu-eCommerce Analysis

22. The future lies in NLP, without
which many advancing
technological fields may NOT
progress.
Thank you.