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Practical Natural Language Processing
From Theory to Industrial Applications
Jaganadh G
http://jaganadhg.in
jaganadhg@gmail.com
Central University of Kerala
Kasargod
22nd
Feb 2013
Jaganadh G Practical Natural Language Processing
About me !!
Working in Natural Language Processing, Machine
Learning, Data Mining etc...
Passionate about Free and Open source :-)
When gets free time teaches Python, Speaks about FOSS
and blogs at
http://jaganadhg.in
I am a computational linguist / Linguist and Indologist,
Book reviewer
Software Engineer by Profession
Jaganadh G Practical Natural Language Processing
Question ??
Have you ever used any Natural Language Processing based
tools/services?
Jaganadh G Practical Natural Language Processing
Question ??
Have you ever used any Natural Language Processing based
tools/services?
Jaganadh G Practical Natural Language Processing
Question ??
Have you ever used any Natural Language Processing based
tools/services?
Jaganadh G Practical Natural Language Processing
What is Natural Language Processing (NLP) ?
Aim : To build intelligent systems that can interact with
human beings as like human beings
Jaganadh G Practical Natural Language Processing
What is Natural Language Processing (NLP) ?
Aim : To build intelligent systems that can interact with
human beings as like human beings
Jaganadh G Practical Natural Language Processing
What is Natural Language Processing (NLP) ?
Aim : To build intelligent systems that can interact with
human beings as like human beings
A sub-field of Artificial Intelligence (AI)
Jaganadh G Practical Natural Language Processing
What is Natural Language Processing (NLP) ?
Aim : To build intelligent systems that can interact with
human beings as like human beings
A sub-field of Artificial Intelligence (AI)
Inter-disciplinary subject (Language + Linguistics +
Statistics + Computer Science + .. )
Natural Language
Refers to the language spoken by people, e.g.
English,Japanese, Tamil, Malayalam as opposed to artificial
languages, like C++, Java, etc.
Jaganadh G Practical Natural Language Processing
Definition
Natural Language Processing
Natural Language Processing is a theoretically motivated range
of computational techniques for analyzing 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.
NLP was considered as an academic discipline before
some 10 to 20 years.
Now concepts from NLP is applied in variety of
Computing Platforms and Services
Jaganadh G Practical Natural Language Processing
Practical NLP ?
Problem
Picture Courtesy: http://twitpic.com/1y21qm/full
Jaganadh G Practical Natural Language Processing
Practical NLP ?
Problem
Before going to some theory can we have some funny
practical problems to solve ?
Picture Courtesy: http://twitpic.com/1y21qm/full
Jaganadh G Practical Natural Language Processing
Practical NLP ?
Problem
Before going to some theory can we have some funny
practical problems to solve ?
Picture Courtesy: http://twitpic.com/1y21qm/full
Jaganadh G Practical Natural Language Processing
Practical NLP
Problem
Jaganadh G Practical Natural Language Processing
Practical NLP
Problem
Tweet-a-Toddy receives thousands of tweets per day
Jaganadh G Practical Natural Language Processing
Practical NLP
Problem
Tweet-a-Toddy receives thousands of tweets per day
Tweets requesting home delivery
Jaganadh G Practical Natural Language Processing
Practical NLP
Problem
Tweet-a-Toddy receives thousands of tweets per day
Tweets requesting home delivery
Tweets about quality of products
Jaganadh G Practical Natural Language Processing
Practical NLP
Problem
Tweet-a-Toddy receives thousands of tweets per day
Tweets requesting home delivery
Tweets about quality of products
Tweets related to enquirers
Jaganadh G Practical Natural Language Processing
Practical NLP
Problem
Tweet-a-Toddy receives thousands of tweets per day
Tweets requesting home delivery
Tweets about quality of products
Tweets related to enquirers
They requires following things to be automated
Jaganadh G Practical Natural Language Processing
Practical NLP
Problem
Tweet-a-Toddy receives thousands of tweets per day
Tweets requesting home delivery
Tweets about quality of products
Tweets related to enquirers
They requires following things to be automated
Identify tweet category
Jaganadh G Practical Natural Language Processing
Practical NLP
Problem
Tweet-a-Toddy receives thousands of tweets per day
Tweets requesting home delivery
Tweets about quality of products
Tweets related to enquirers
They requires following things to be automated
Identify tweet category
Process home-delivery request
Jaganadh G Practical Natural Language Processing
Practical NLP
Problem
Tweet-a-Toddy receives thousands of tweets per day
Tweets requesting home delivery
Tweets about quality of products
Tweets related to enquirers
They requires following things to be automated
Identify tweet category
Process home-delivery request
Evaluate quality related tweets
Jaganadh G Practical Natural Language Processing
Practical NLP
Problem
Tweet-a-Toddy receives thousands of tweets per day
Tweets requesting home delivery
Tweets about quality of products
Tweets related to enquirers
They requires following things to be automated
Identify tweet category
Process home-delivery request
Evaluate quality related tweets
How?
How to find a solution for Tweet-a-Toddy
Jaganadh G Practical Natural Language Processing
Solution
??
Any Solutions
Jaganadh G Practical Natural Language Processing
Solution
??
Any Solutions
Some thoughts
Jaganadh G Practical Natural Language Processing
Solution
??
Any Solutions
Some thoughts
Text Classification
Jaganadh G Practical Natural Language Processing
Solution
??
Any Solutions
Some thoughts
Text Classification
Entity Identification
Jaganadh G Practical Natural Language Processing
Solution
??
Any Solutions
Some thoughts
Text Classification
Entity Identification
Information Extraction
Jaganadh G Practical Natural Language Processing
Solution
??
Any Solutions
Some thoughts
Text Classification
Entity Identification
Information Extraction
Sentiment Analysis
Jaganadh G Practical Natural Language Processing
Solution
??
Any Solutions
Some thoughts
Text Classification
Entity Identification
Information Extraction
Sentiment Analysis
Parsing, gammer ...
Jaganadh G Practical Natural Language Processing
Solution
??
Any Solutions
Some thoughts
Text Classification
Entity Identification
Information Extraction
Sentiment Analysis
Parsing, gammer ...
Regex (Regular Expressions)
Jaganadh G Practical Natural Language Processing
Another Practical Question
Everybody might have used spell checker available in word
processing systems like OpenOffice.org or Microsoft Word Any
guess on how to develop a spell checker system ?
Solutions
Jaganadh G Practical Natural Language Processing
Another Practical Question
Everybody might have used spell checker available in word
processing systems like OpenOffice.org or Microsoft Word Any
guess on how to develop a spell checker system ?
Solutions
Word List
Jaganadh G Practical Natural Language Processing
Another Practical Question
Everybody might have used spell checker available in word
processing systems like OpenOffice.org or Microsoft Word Any
guess on how to develop a spell checker system ?
Solutions
Word List
Structure of words
Jaganadh G Practical Natural Language Processing
Another Practical Question
Everybody might have used spell checker available in word
processing systems like OpenOffice.org or Microsoft Word Any
guess on how to develop a spell checker system ?
Solutions
Word List
Structure of words
Dynamic Programming (Edit Distance)
Jaganadh G Practical Natural Language Processing
Another Practical Question ...
Context Sensitive Spell-checking
Identifying and suggesting spelling of words based on context
How ??
Jaganadh G Practical Natural Language Processing
Another Practical Question ...
Context Sensitive Spell-checking
Identifying and suggesting spelling of words based on context
How ??
Solutions
Jaganadh G Practical Natural Language Processing
Another Practical Question ...
Context Sensitive Spell-checking
Identifying and suggesting spelling of words based on context
How ??
Solutions
Statistical Models
Jaganadh G Practical Natural Language Processing
Another Practical Question ...
Context Sensitive Spell-checking
Identifying and suggesting spelling of words based on context
How ??
Solutions
Statistical Models
Word category based suggestions
Jaganadh G Practical Natural Language Processing
Can Machines Translate ??
Answer !!!
Jaganadh G Practical Natural Language Processing
Why NLP ?
Because ”Information is Power !!!”
Jaganadh G Practical Natural Language Processing
Why NLP ?
Because ”Information is Power !!!”
Picture Courtesy: http://soundsgood.in/wikipediafat print book/
Jaganadh G Practical Natural Language Processing
Why NLP ?
Because ”Information is Power !!!”
Every day wast amount of text and speech data is being
produced
Picture Courtesy: http://soundsgood.in/wikipediafat print book/
Jaganadh G Practical Natural Language Processing
Why NLP ?
Because ”Information is Power !!!”
Every day wast amount of text and speech data is being
produced
Internet == at least 40 Million pages
Picture Courtesy: http://soundsgood.in/wikipediafat print book/
Jaganadh G Practical Natural Language Processing
Why NLP ?
Because ”Information is Power !!!”
Every day wast amount of text and speech data is being
produced
Internet == at least 40 Million pages
Picture Courtesy: http://soundsgood.in/wikipediafat print book/
Jaganadh G Practical Natural Language Processing
History
Jaganadh G Practical Natural Language Processing
History
Second World War !!!
Jaganadh G Practical Natural Language Processing
History
Second World War !!!
Machine Translation
Jaganadh G Practical Natural Language Processing
History
Second World War !!!
Machine Translation
Now :
Jaganadh G Practical Natural Language Processing
History
Second World War !!!
Machine Translation
Now :
Most promising imperfect technology
Jaganadh G Practical Natural Language Processing
History
Second World War !!!
Machine Translation
Now :
Most promising imperfect technology
Moves from Lab to Industry to Layman
Jaganadh G Practical Natural Language Processing
NLP Really Hard to Achieve?
NLP delas with human languages
Human Language is dynamic and mysterious !!!
Jaganadh G Practical Natural Language Processing
NLP Really Hard to Achieve?
NLP delas with human languages
Human Language is dynamic and mysterious !!!
Communication in Human Language
Jaganadh G Practical Natural Language Processing
NLP Really Hard to Achieve?
Levels of Knowledge encoding in Language Data
Jaganadh G Practical Natural Language Processing
Tasks in NLP
Broad Areas
Jaganadh G Practical Natural Language Processing
Tasks in NLP
Broad Areas
Text Processing
Jaganadh G Practical Natural Language Processing
Tasks in NLP
Broad Areas
Text Processing
Speech Processing
Jaganadh G Practical Natural Language Processing
Major tasks in Text Processing
Jaganadh G Practical Natural Language Processing
Major tasks in Text Processing
Word Level Analysis
Jaganadh G Practical Natural Language Processing
Major tasks in Text Processing
Word Level Analysis
Morphological Synthesis
Jaganadh G Practical Natural Language Processing
Major tasks in Text Processing
Word Level Analysis
Morphological Synthesis
Part of Speech Tagging
Jaganadh G Practical Natural Language Processing
Major tasks in Text Processing
Word Level Analysis
Morphological Synthesis
Part of Speech Tagging
Stemming
Jaganadh G Practical Natural Language Processing
Major tasks in Text Processing
Word Level Analysis
Morphological Synthesis
Part of Speech Tagging
Stemming
Lemmatization
Jaganadh G Practical Natural Language Processing
Major tasks in Text Processing
Word Level Analysis
Morphological Synthesis
Part of Speech Tagging
Stemming
Lemmatization
Sentence Level Analysis - Syntactical Parsing
Jaganadh G Practical Natural Language Processing
Major tasks in Text Processing
Word Level Analysis
Morphological Synthesis
Part of Speech Tagging
Stemming
Lemmatization
Sentence Level Analysis - Syntactical Parsing
Discourse Analysis - Semantic Processing
Jaganadh G Practical Natural Language Processing
Morphology
The branch of linguistics that studies word structures.
Jaganadh G Practical Natural Language Processing
Morphology
The branch of linguistics that studies word structures.
To a computer program a word is : ???
Jaganadh G Practical Natural Language Processing
Morphology
The branch of linguistics that studies word structures.
To a computer program a word is : ???
Morphological analysis can be explained as: the process of
analyzing words to identify its constituents
Jaganadh G Practical Natural Language Processing
Morphology
The branch of linguistics that studies word structures.
To a computer program a word is : ???
Morphological analysis can be explained as: the process of
analyzing words to identify its constituents
Computational Analysis of Morphology
Morphological Analysis
Jaganadh G Practical Natural Language Processing
Morphology
The branch of linguistics that studies word structures.
To a computer program a word is : ???
Morphological analysis can be explained as: the process of
analyzing words to identify its constituents
Computational Analysis of Morphology
Morphological Analysis
Jaganadh G Practical Natural Language Processing
Morphology
The branch of linguistics that studies word structures.
To a computer program a word is : ???
Morphological analysis can be explained as: the process of
analyzing words to identify its constituents
Computational Analysis of Morphology
Morphological Analysis
Morphological Generation
Jaganadh G Practical Natural Language Processing
Morphology
The branch of linguistics that studies word structures.
To a computer program a word is : ???
Morphological analysis can be explained as: the process of
analyzing words to identify its constituents
Computational Analysis of Morphology
Morphological Analysis
Morphological Generation
Stemming
Jaganadh G Practical Natural Language Processing
Morphology
The branch of linguistics that studies word structures.
To a computer program a word is : ???
Morphological analysis can be explained as: the process of
analyzing words to identify its constituents
Computational Analysis of Morphology
Morphological Analysis
Morphological Generation
Stemming
Lemmatization
Jaganadh G Practical Natural Language Processing
Practical Question from Morphology
Approximate number of word forms that can be derived from
the word
”maram”
Jaganadh G Practical Natural Language Processing
Parts of Speech Tagging
POS tagging is the process of marking up the words in a text
(corpus) as corresponding to a particular part of speech, based
on both its definition, as well as its context.
Ram goes to school.
Ram/NNP goes/VBZ to/TO school/NN ./.
Jaganadh G Practical Natural Language Processing
Parts of Speech Tagging
POS tagging is the process of marking up the words in a text
(corpus) as corresponding to a particular part of speech, based
on both its definition, as well as its context.
Ram goes to school.
Ram/NNP goes/VBZ to/TO school/NN ./.
Words are ambiguous !!!!
e.g. book, cricket, bank
Jaganadh G Practical Natural Language Processing
Syntactical Parsing
Parsing
In computer science and linguistics, parsing, or, more formally,
syntactic analysis, is the process of analyzing a text, made of a
sequence of tokens (for example, words), to determine its
grammatical structure with respect to a given (more or less)
formal grammar.
Jaganadh G Practical Natural Language Processing
Syntactical Parsing
Parsing
In computer science and linguistics, parsing, or, more formally,
syntactic analysis, is the process of analyzing a text, made of a
sequence of tokens (for example, words), to determine its
grammatical structure with respect to a given (more or less)
formal grammar.
Sentences are ambiguous !!!!
Jaganadh G Practical Natural Language Processing
Semantics
Study of meaning ans its structure
Jaganadh G Practical Natural Language Processing
Semantics
Study of meaning ans its structure
Word meaning is ambiguous !!!!
E.g. marriage
Jaganadh G Practical Natural Language Processing
Where can I apply this techniques?
Machine Translation Systems
Jaganadh G Practical Natural Language Processing
Where can I apply this techniques?
Machine Translation Systems
Search Engine
Jaganadh G Practical Natural Language Processing
Where can I apply this techniques?
Machine Translation Systems
Search Engine
Spell-checker
Jaganadh G Practical Natural Language Processing
Where can I apply this techniques?
Machine Translation Systems
Search Engine
Spell-checker
Grammar Checker
Jaganadh G Practical Natural Language Processing
Where can I apply this techniques?
Machine Translation Systems
Search Engine
Spell-checker
Grammar Checker
..........
Jaganadh G Practical Natural Language Processing
Other Interesting Tasks
Named Entity Identification
Jaganadh G Practical Natural Language Processing
Other Interesting Tasks
Named Entity Identification
Information Extraction
Jaganadh G Practical Natural Language Processing
Other Interesting Tasks
Named Entity Identification
Information Extraction
Information Retrieval
Jaganadh G Practical Natural Language Processing
Other Interesting Tasks
Named Entity Identification
Information Extraction
Information Retrieval
Text Classification and Clustering
Jaganadh G Practical Natural Language Processing
Speech Processing
Two Major Areas
Text to Speech
Speech Recognition
Jaganadh G Practical Natural Language Processing
Speech Processing
Two Major Areas
Text to Speech
Speech Recognition
Practical Applications
IVR
Technology for Visually Challenged People
Mobile Phones
Speech Enabled Web
Vehicle Mounted GPS Navigator
Jaganadh G Practical Natural Language Processing
Commerical NLP Applications
What Industry Looks
Jaganadh G Practical Natural Language Processing
Commerical NLP Applications
What Industry Looks
Components of Word Processors
Jaganadh G Practical Natural Language Processing
Commerical NLP Applications
What Industry Looks
Components of Word Processors
Machine Translation Systems
Jaganadh G Practical Natural Language Processing
Commerical NLP Applications
What Industry Looks
Components of Word Processors
Machine Translation Systems
Custom Search Systems
Jaganadh G Practical Natural Language Processing
Commerical NLP Applications
What Industry Looks
Components of Word Processors
Machine Translation Systems
Custom Search Systems
Information Extraction
Jaganadh G Practical Natural Language Processing
Commerical NLP Applications
What Industry Looks
Components of Word Processors
Machine Translation Systems
Custom Search Systems
Information Extraction
Entity Identification
Jaganadh G Practical Natural Language Processing
Commerical NLP Applications
What Industry Looks
Components of Word Processors
Machine Translation Systems
Custom Search Systems
Information Extraction
Entity Identification
Text Summarization
Jaganadh G Practical Natural Language Processing
Commerical NLP Applications
What Industry Looks
Components of Word Processors
Machine Translation Systems
Custom Search Systems
Information Extraction
Entity Identification
Text Summarization
Speech Systems
Jaganadh G Practical Natural Language Processing
Commerical NLP Applications
What Industry Looks
Components of Word Processors
Machine Translation Systems
Custom Search Systems
Information Extraction
Entity Identification
Text Summarization
Speech Systems
Question Answering Systems
Jaganadh G Practical Natural Language Processing
Future of NLP
Future!!!
Semantics oriented technologies
Jaganadh G Practical Natural Language Processing
NLP in other domains
Bio-Medical
Legal
Forensic Science
Advertisement
Education
Politics
E-governance
Business Development
Marketing
and where ever we use language !!!
Jaganadh G Practical Natural Language Processing
Natural Language Processing in India
Academic Institutions
IIT Kanpur, Kharagpur, Bombay
IIIT hydrabad
IISc Bangalore
AU-KBC Chennai
Amritha University Ettimadai, Coimbatore
IIITMK, Trivandrum
Central University, Hydrabad
JNU, Delhi
Tamil University, Thanjore
Jaganadh G Practical Natural Language Processing
Natural Language Processing in India
Industry
Microsoft
Yahoo!
AOL
365Media Pvt. Ltd.
Inside View
Thaazza
AIAIO Labs
Jaganadh G Practical Natural Language Processing
Questions ??
Jaganadh G Practical Natural Language Processing
References
Daniel Jurafsky,James H. Martin, SPEECH and
LANGUAGE PROCESSING, 2nd
Edition.
U.S. Tiwary, Tanveer Siddiqui , Natural Language
Processing and Information Retrieval
Jaganadh G Practical Natural Language Processing
Finally
Jaganadh G Practical Natural Language Processing
Questions ??
Jaganadh G Practical Natural Language Processing
References
Daniel Jurafsky,James H. Martin, SPEECH and
LANGUAGE PROCESSING, 2nd
Edition.
U.S. Tiwary, Tanveer Siddiqui , Natural Language
Processing and Information Retrieval
Jaganadh G Practical Natural Language Processing
Finally
Jaganadh G Practical Natural Language Processing

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Practical Natural Language Processing

  • 1. Practical Natural Language Processing From Theory to Industrial Applications Jaganadh G http://jaganadhg.in jaganadhg@gmail.com Central University of Kerala Kasargod 22nd Feb 2013 Jaganadh G Practical Natural Language Processing
  • 2. About me !! Working in Natural Language Processing, Machine Learning, Data Mining etc... Passionate about Free and Open source :-) When gets free time teaches Python, Speaks about FOSS and blogs at http://jaganadhg.in I am a computational linguist / Linguist and Indologist, Book reviewer Software Engineer by Profession Jaganadh G Practical Natural Language Processing
  • 3. Question ?? Have you ever used any Natural Language Processing based tools/services? Jaganadh G Practical Natural Language Processing
  • 4. Question ?? Have you ever used any Natural Language Processing based tools/services? Jaganadh G Practical Natural Language Processing
  • 5. Question ?? Have you ever used any Natural Language Processing based tools/services? Jaganadh G Practical Natural Language Processing
  • 6. What is Natural Language Processing (NLP) ? Aim : To build intelligent systems that can interact with human beings as like human beings Jaganadh G Practical Natural Language Processing
  • 7. What is Natural Language Processing (NLP) ? Aim : To build intelligent systems that can interact with human beings as like human beings Jaganadh G Practical Natural Language Processing
  • 8. What is Natural Language Processing (NLP) ? Aim : To build intelligent systems that can interact with human beings as like human beings A sub-field of Artificial Intelligence (AI) Jaganadh G Practical Natural Language Processing
  • 9. What is Natural Language Processing (NLP) ? Aim : To build intelligent systems that can interact with human beings as like human beings A sub-field of Artificial Intelligence (AI) Inter-disciplinary subject (Language + Linguistics + Statistics + Computer Science + .. ) Natural Language Refers to the language spoken by people, e.g. English,Japanese, Tamil, Malayalam as opposed to artificial languages, like C++, Java, etc. Jaganadh G Practical Natural Language Processing
  • 10. Definition Natural Language Processing Natural Language Processing is a theoretically motivated range of computational techniques for analyzing 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. NLP was considered as an academic discipline before some 10 to 20 years. Now concepts from NLP is applied in variety of Computing Platforms and Services Jaganadh G Practical Natural Language Processing
  • 11. Practical NLP ? Problem Picture Courtesy: http://twitpic.com/1y21qm/full Jaganadh G Practical Natural Language Processing
  • 12. Practical NLP ? Problem Before going to some theory can we have some funny practical problems to solve ? Picture Courtesy: http://twitpic.com/1y21qm/full Jaganadh G Practical Natural Language Processing
  • 13. Practical NLP ? Problem Before going to some theory can we have some funny practical problems to solve ? Picture Courtesy: http://twitpic.com/1y21qm/full Jaganadh G Practical Natural Language Processing
  • 14. Practical NLP Problem Jaganadh G Practical Natural Language Processing
  • 15. Practical NLP Problem Tweet-a-Toddy receives thousands of tweets per day Jaganadh G Practical Natural Language Processing
  • 16. Practical NLP Problem Tweet-a-Toddy receives thousands of tweets per day Tweets requesting home delivery Jaganadh G Practical Natural Language Processing
  • 17. Practical NLP Problem Tweet-a-Toddy receives thousands of tweets per day Tweets requesting home delivery Tweets about quality of products Jaganadh G Practical Natural Language Processing
  • 18. Practical NLP Problem Tweet-a-Toddy receives thousands of tweets per day Tweets requesting home delivery Tweets about quality of products Tweets related to enquirers Jaganadh G Practical Natural Language Processing
  • 19. Practical NLP Problem Tweet-a-Toddy receives thousands of tweets per day Tweets requesting home delivery Tweets about quality of products Tweets related to enquirers They requires following things to be automated Jaganadh G Practical Natural Language Processing
  • 20. Practical NLP Problem Tweet-a-Toddy receives thousands of tweets per day Tweets requesting home delivery Tweets about quality of products Tweets related to enquirers They requires following things to be automated Identify tweet category Jaganadh G Practical Natural Language Processing
  • 21. Practical NLP Problem Tweet-a-Toddy receives thousands of tweets per day Tweets requesting home delivery Tweets about quality of products Tweets related to enquirers They requires following things to be automated Identify tweet category Process home-delivery request Jaganadh G Practical Natural Language Processing
  • 22. Practical NLP Problem Tweet-a-Toddy receives thousands of tweets per day Tweets requesting home delivery Tweets about quality of products Tweets related to enquirers They requires following things to be automated Identify tweet category Process home-delivery request Evaluate quality related tweets Jaganadh G Practical Natural Language Processing
  • 23. Practical NLP Problem Tweet-a-Toddy receives thousands of tweets per day Tweets requesting home delivery Tweets about quality of products Tweets related to enquirers They requires following things to be automated Identify tweet category Process home-delivery request Evaluate quality related tweets How? How to find a solution for Tweet-a-Toddy Jaganadh G Practical Natural Language Processing
  • 24. Solution ?? Any Solutions Jaganadh G Practical Natural Language Processing
  • 25. Solution ?? Any Solutions Some thoughts Jaganadh G Practical Natural Language Processing
  • 26. Solution ?? Any Solutions Some thoughts Text Classification Jaganadh G Practical Natural Language Processing
  • 27. Solution ?? Any Solutions Some thoughts Text Classification Entity Identification Jaganadh G Practical Natural Language Processing
  • 28. Solution ?? Any Solutions Some thoughts Text Classification Entity Identification Information Extraction Jaganadh G Practical Natural Language Processing
  • 29. Solution ?? Any Solutions Some thoughts Text Classification Entity Identification Information Extraction Sentiment Analysis Jaganadh G Practical Natural Language Processing
  • 30. Solution ?? Any Solutions Some thoughts Text Classification Entity Identification Information Extraction Sentiment Analysis Parsing, gammer ... Jaganadh G Practical Natural Language Processing
  • 31. Solution ?? Any Solutions Some thoughts Text Classification Entity Identification Information Extraction Sentiment Analysis Parsing, gammer ... Regex (Regular Expressions) Jaganadh G Practical Natural Language Processing
  • 32. Another Practical Question Everybody might have used spell checker available in word processing systems like OpenOffice.org or Microsoft Word Any guess on how to develop a spell checker system ? Solutions Jaganadh G Practical Natural Language Processing
  • 33. Another Practical Question Everybody might have used spell checker available in word processing systems like OpenOffice.org or Microsoft Word Any guess on how to develop a spell checker system ? Solutions Word List Jaganadh G Practical Natural Language Processing
  • 34. Another Practical Question Everybody might have used spell checker available in word processing systems like OpenOffice.org or Microsoft Word Any guess on how to develop a spell checker system ? Solutions Word List Structure of words Jaganadh G Practical Natural Language Processing
  • 35. Another Practical Question Everybody might have used spell checker available in word processing systems like OpenOffice.org or Microsoft Word Any guess on how to develop a spell checker system ? Solutions Word List Structure of words Dynamic Programming (Edit Distance) Jaganadh G Practical Natural Language Processing
  • 36. Another Practical Question ... Context Sensitive Spell-checking Identifying and suggesting spelling of words based on context How ?? Jaganadh G Practical Natural Language Processing
  • 37. Another Practical Question ... Context Sensitive Spell-checking Identifying and suggesting spelling of words based on context How ?? Solutions Jaganadh G Practical Natural Language Processing
  • 38. Another Practical Question ... Context Sensitive Spell-checking Identifying and suggesting spelling of words based on context How ?? Solutions Statistical Models Jaganadh G Practical Natural Language Processing
  • 39. Another Practical Question ... Context Sensitive Spell-checking Identifying and suggesting spelling of words based on context How ?? Solutions Statistical Models Word category based suggestions Jaganadh G Practical Natural Language Processing
  • 40. Can Machines Translate ?? Answer !!! Jaganadh G Practical Natural Language Processing
  • 41. Why NLP ? Because ”Information is Power !!!” Jaganadh G Practical Natural Language Processing
  • 42. Why NLP ? Because ”Information is Power !!!” Picture Courtesy: http://soundsgood.in/wikipediafat print book/ Jaganadh G Practical Natural Language Processing
  • 43. Why NLP ? Because ”Information is Power !!!” Every day wast amount of text and speech data is being produced Picture Courtesy: http://soundsgood.in/wikipediafat print book/ Jaganadh G Practical Natural Language Processing
  • 44. Why NLP ? Because ”Information is Power !!!” Every day wast amount of text and speech data is being produced Internet == at least 40 Million pages Picture Courtesy: http://soundsgood.in/wikipediafat print book/ Jaganadh G Practical Natural Language Processing
  • 45. Why NLP ? Because ”Information is Power !!!” Every day wast amount of text and speech data is being produced Internet == at least 40 Million pages Picture Courtesy: http://soundsgood.in/wikipediafat print book/ Jaganadh G Practical Natural Language Processing
  • 46. History Jaganadh G Practical Natural Language Processing
  • 47. History Second World War !!! Jaganadh G Practical Natural Language Processing
  • 48. History Second World War !!! Machine Translation Jaganadh G Practical Natural Language Processing
  • 49. History Second World War !!! Machine Translation Now : Jaganadh G Practical Natural Language Processing
  • 50. History Second World War !!! Machine Translation Now : Most promising imperfect technology Jaganadh G Practical Natural Language Processing
  • 51. History Second World War !!! Machine Translation Now : Most promising imperfect technology Moves from Lab to Industry to Layman Jaganadh G Practical Natural Language Processing
  • 52. NLP Really Hard to Achieve? NLP delas with human languages Human Language is dynamic and mysterious !!! Jaganadh G Practical Natural Language Processing
  • 53. NLP Really Hard to Achieve? NLP delas with human languages Human Language is dynamic and mysterious !!! Communication in Human Language Jaganadh G Practical Natural Language Processing
  • 54. NLP Really Hard to Achieve? Levels of Knowledge encoding in Language Data Jaganadh G Practical Natural Language Processing
  • 55. Tasks in NLP Broad Areas Jaganadh G Practical Natural Language Processing
  • 56. Tasks in NLP Broad Areas Text Processing Jaganadh G Practical Natural Language Processing
  • 57. Tasks in NLP Broad Areas Text Processing Speech Processing Jaganadh G Practical Natural Language Processing
  • 58. Major tasks in Text Processing Jaganadh G Practical Natural Language Processing
  • 59. Major tasks in Text Processing Word Level Analysis Jaganadh G Practical Natural Language Processing
  • 60. Major tasks in Text Processing Word Level Analysis Morphological Synthesis Jaganadh G Practical Natural Language Processing
  • 61. Major tasks in Text Processing Word Level Analysis Morphological Synthesis Part of Speech Tagging Jaganadh G Practical Natural Language Processing
  • 62. Major tasks in Text Processing Word Level Analysis Morphological Synthesis Part of Speech Tagging Stemming Jaganadh G Practical Natural Language Processing
  • 63. Major tasks in Text Processing Word Level Analysis Morphological Synthesis Part of Speech Tagging Stemming Lemmatization Jaganadh G Practical Natural Language Processing
  • 64. Major tasks in Text Processing Word Level Analysis Morphological Synthesis Part of Speech Tagging Stemming Lemmatization Sentence Level Analysis - Syntactical Parsing Jaganadh G Practical Natural Language Processing
  • 65. Major tasks in Text Processing Word Level Analysis Morphological Synthesis Part of Speech Tagging Stemming Lemmatization Sentence Level Analysis - Syntactical Parsing Discourse Analysis - Semantic Processing Jaganadh G Practical Natural Language Processing
  • 66. Morphology The branch of linguistics that studies word structures. Jaganadh G Practical Natural Language Processing
  • 67. Morphology The branch of linguistics that studies word structures. To a computer program a word is : ??? Jaganadh G Practical Natural Language Processing
  • 68. Morphology The branch of linguistics that studies word structures. To a computer program a word is : ??? Morphological analysis can be explained as: the process of analyzing words to identify its constituents Jaganadh G Practical Natural Language Processing
  • 69. Morphology The branch of linguistics that studies word structures. To a computer program a word is : ??? Morphological analysis can be explained as: the process of analyzing words to identify its constituents Computational Analysis of Morphology Morphological Analysis Jaganadh G Practical Natural Language Processing
  • 70. Morphology The branch of linguistics that studies word structures. To a computer program a word is : ??? Morphological analysis can be explained as: the process of analyzing words to identify its constituents Computational Analysis of Morphology Morphological Analysis Jaganadh G Practical Natural Language Processing
  • 71. Morphology The branch of linguistics that studies word structures. To a computer program a word is : ??? Morphological analysis can be explained as: the process of analyzing words to identify its constituents Computational Analysis of Morphology Morphological Analysis Morphological Generation Jaganadh G Practical Natural Language Processing
  • 72. Morphology The branch of linguistics that studies word structures. To a computer program a word is : ??? Morphological analysis can be explained as: the process of analyzing words to identify its constituents Computational Analysis of Morphology Morphological Analysis Morphological Generation Stemming Jaganadh G Practical Natural Language Processing
  • 73. Morphology The branch of linguistics that studies word structures. To a computer program a word is : ??? Morphological analysis can be explained as: the process of analyzing words to identify its constituents Computational Analysis of Morphology Morphological Analysis Morphological Generation Stemming Lemmatization Jaganadh G Practical Natural Language Processing
  • 74. Practical Question from Morphology Approximate number of word forms that can be derived from the word ”maram” Jaganadh G Practical Natural Language Processing
  • 75. Parts of Speech Tagging POS tagging is the process of marking up the words in a text (corpus) as corresponding to a particular part of speech, based on both its definition, as well as its context. Ram goes to school. Ram/NNP goes/VBZ to/TO school/NN ./. Jaganadh G Practical Natural Language Processing
  • 76. Parts of Speech Tagging POS tagging is the process of marking up the words in a text (corpus) as corresponding to a particular part of speech, based on both its definition, as well as its context. Ram goes to school. Ram/NNP goes/VBZ to/TO school/NN ./. Words are ambiguous !!!! e.g. book, cricket, bank Jaganadh G Practical Natural Language Processing
  • 77. Syntactical Parsing Parsing In computer science and linguistics, parsing, or, more formally, syntactic analysis, is the process of analyzing a text, made of a sequence of tokens (for example, words), to determine its grammatical structure with respect to a given (more or less) formal grammar. Jaganadh G Practical Natural Language Processing
  • 78. Syntactical Parsing Parsing In computer science and linguistics, parsing, or, more formally, syntactic analysis, is the process of analyzing a text, made of a sequence of tokens (for example, words), to determine its grammatical structure with respect to a given (more or less) formal grammar. Sentences are ambiguous !!!! Jaganadh G Practical Natural Language Processing
  • 79. Semantics Study of meaning ans its structure Jaganadh G Practical Natural Language Processing
  • 80. Semantics Study of meaning ans its structure Word meaning is ambiguous !!!! E.g. marriage Jaganadh G Practical Natural Language Processing
  • 81. Where can I apply this techniques? Machine Translation Systems Jaganadh G Practical Natural Language Processing
  • 82. Where can I apply this techniques? Machine Translation Systems Search Engine Jaganadh G Practical Natural Language Processing
  • 83. Where can I apply this techniques? Machine Translation Systems Search Engine Spell-checker Jaganadh G Practical Natural Language Processing
  • 84. Where can I apply this techniques? Machine Translation Systems Search Engine Spell-checker Grammar Checker Jaganadh G Practical Natural Language Processing
  • 85. Where can I apply this techniques? Machine Translation Systems Search Engine Spell-checker Grammar Checker .......... Jaganadh G Practical Natural Language Processing
  • 86. Other Interesting Tasks Named Entity Identification Jaganadh G Practical Natural Language Processing
  • 87. Other Interesting Tasks Named Entity Identification Information Extraction Jaganadh G Practical Natural Language Processing
  • 88. Other Interesting Tasks Named Entity Identification Information Extraction Information Retrieval Jaganadh G Practical Natural Language Processing
  • 89. Other Interesting Tasks Named Entity Identification Information Extraction Information Retrieval Text Classification and Clustering Jaganadh G Practical Natural Language Processing
  • 90. Speech Processing Two Major Areas Text to Speech Speech Recognition Jaganadh G Practical Natural Language Processing
  • 91. Speech Processing Two Major Areas Text to Speech Speech Recognition Practical Applications IVR Technology for Visually Challenged People Mobile Phones Speech Enabled Web Vehicle Mounted GPS Navigator Jaganadh G Practical Natural Language Processing
  • 92. Commerical NLP Applications What Industry Looks Jaganadh G Practical Natural Language Processing
  • 93. Commerical NLP Applications What Industry Looks Components of Word Processors Jaganadh G Practical Natural Language Processing
  • 94. Commerical NLP Applications What Industry Looks Components of Word Processors Machine Translation Systems Jaganadh G Practical Natural Language Processing
  • 95. Commerical NLP Applications What Industry Looks Components of Word Processors Machine Translation Systems Custom Search Systems Jaganadh G Practical Natural Language Processing
  • 96. Commerical NLP Applications What Industry Looks Components of Word Processors Machine Translation Systems Custom Search Systems Information Extraction Jaganadh G Practical Natural Language Processing
  • 97. Commerical NLP Applications What Industry Looks Components of Word Processors Machine Translation Systems Custom Search Systems Information Extraction Entity Identification Jaganadh G Practical Natural Language Processing
  • 98. Commerical NLP Applications What Industry Looks Components of Word Processors Machine Translation Systems Custom Search Systems Information Extraction Entity Identification Text Summarization Jaganadh G Practical Natural Language Processing
  • 99. Commerical NLP Applications What Industry Looks Components of Word Processors Machine Translation Systems Custom Search Systems Information Extraction Entity Identification Text Summarization Speech Systems Jaganadh G Practical Natural Language Processing
  • 100. Commerical NLP Applications What Industry Looks Components of Word Processors Machine Translation Systems Custom Search Systems Information Extraction Entity Identification Text Summarization Speech Systems Question Answering Systems Jaganadh G Practical Natural Language Processing
  • 101. Future of NLP Future!!! Semantics oriented technologies Jaganadh G Practical Natural Language Processing
  • 102. NLP in other domains Bio-Medical Legal Forensic Science Advertisement Education Politics E-governance Business Development Marketing and where ever we use language !!! Jaganadh G Practical Natural Language Processing
  • 103. Natural Language Processing in India Academic Institutions IIT Kanpur, Kharagpur, Bombay IIIT hydrabad IISc Bangalore AU-KBC Chennai Amritha University Ettimadai, Coimbatore IIITMK, Trivandrum Central University, Hydrabad JNU, Delhi Tamil University, Thanjore Jaganadh G Practical Natural Language Processing
  • 104. Natural Language Processing in India Industry Microsoft Yahoo! AOL 365Media Pvt. Ltd. Inside View Thaazza AIAIO Labs Jaganadh G Practical Natural Language Processing
  • 105. Questions ?? Jaganadh G Practical Natural Language Processing
  • 106. References Daniel Jurafsky,James H. Martin, SPEECH and LANGUAGE PROCESSING, 2nd Edition. U.S. Tiwary, Tanveer Siddiqui , Natural Language Processing and Information Retrieval Jaganadh G Practical Natural Language Processing
  • 107. Finally Jaganadh G Practical Natural Language Processing
  • 108. Questions ?? Jaganadh G Practical Natural Language Processing
  • 109. References Daniel Jurafsky,James H. Martin, SPEECH and LANGUAGE PROCESSING, 2nd Edition. U.S. Tiwary, Tanveer Siddiqui , Natural Language Processing and Information Retrieval Jaganadh G Practical Natural Language Processing
  • 110. Finally Jaganadh G Practical Natural Language Processing