![Page 1: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/1.jpg)
Practical Natural Language ProcessingFrom Theory to Industrial Applications
Jaganadh Ghttp://jaganadhg.in
Karpagam UniversityCoimbatore
19th March 2012
Jaganadh G Practical Natural Language Processing
![Page 2: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/2.jpg)
About me !!
Working in Natural Language Processing, MachineLearning, Data Mining etc...
Passionate about Free and Open source :-)
When gets free time teaches Python, Speaks about FOSSand blogs athttp://jaganadhg.in
I am a computational linguist / Linguist and Indologist,Book reviewer
Software Engineer by Profession
Jaganadh G Practical Natural Language Processing
![Page 3: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/3.jpg)
Question ??
Have you ever used any Natural Language Processing basedtools/services?
Jaganadh G Practical Natural Language Processing
![Page 4: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/4.jpg)
Question ??
Have you ever used any Natural Language Processing basedtools/services?
Jaganadh G Practical Natural Language Processing
![Page 5: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/5.jpg)
Question ??
Have you ever used any Natural Language Processing basedtools/services?
Jaganadh G Practical Natural Language Processing
![Page 6: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/6.jpg)
What is Natural Language Processing (NLP) ?
Aim : To build intelligent systems that can interact withhuman 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 artificiallanguages, like C++, Java, etc.
Jaganadh G Practical Natural Language Processing
![Page 7: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/7.jpg)
What is Natural Language Processing (NLP) ?
Aim : To build intelligent systems that can interact withhuman 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 artificiallanguages, like C++, Java, etc.
Jaganadh G Practical Natural Language Processing
![Page 8: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/8.jpg)
What is Natural Language Processing (NLP) ?
Aim : To build intelligent systems that can interact withhuman 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 artificiallanguages, like C++, Java, etc.
Jaganadh G Practical Natural Language Processing
![Page 9: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/9.jpg)
What is Natural Language Processing (NLP) ?
Aim : To build intelligent systems that can interact withhuman 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 artificiallanguages, like C++, Java, etc.
Jaganadh G Practical Natural Language Processing
![Page 10: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/10.jpg)
Definition
Natural Language Processing
Natural Language Processing is a theoretically motivated rangeof computational techniques for analyzing and representingnaturally occurring texts/speech at one or more levels oflinguistic analysis for the purpose of achieving human-likelanguage processing for a range of tasks or applications.
NLP was considered as an academic discipline beforesome 10 to 20 years.
Now concepts from NLP is applied in variety ofComputing Platforms and Services
Jaganadh G Practical Natural Language Processing
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Practical NLP ?
Problem
Before going to some theory can we have some funnypractical problems to solve ?
Picture Courtesy: http://twitpic.com/1y21qm/full
Jaganadh G Practical Natural Language Processing
![Page 12: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/12.jpg)
Practical NLP ?
Problem
Before going to some theory can we have some funnypractical problems to solve ?
Picture Courtesy: http://twitpic.com/1y21qm/full
Jaganadh G Practical Natural Language Processing
![Page 13: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/13.jpg)
Practical NLP ?
Problem
Before going to some theory can we have some funnypractical problems to solve ?
Picture Courtesy: http://twitpic.com/1y21qm/full
Jaganadh G Practical Natural Language Processing
![Page 14: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/14.jpg)
Practical NLP
Problem
Tweet-a-Toddy receives thousands of tweets per day
Tweets requesting home deliveryTweets about quality of productsTweets related to enquirers
They requires following things to be automated
Identify tweet categoryProcess home-delivery requestEvaluate quality related tweets
How?
How to find a solution for Tweet-a-Toddy
Jaganadh G Practical Natural Language Processing
![Page 15: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/15.jpg)
Practical NLP
Problem
Tweet-a-Toddy receives thousands of tweets per day
Tweets requesting home deliveryTweets about quality of productsTweets related to enquirers
They requires following things to be automated
Identify tweet categoryProcess home-delivery requestEvaluate quality related tweets
How?
How to find a solution for Tweet-a-Toddy
Jaganadh G Practical Natural Language Processing
![Page 16: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/16.jpg)
Practical NLP
Problem
Tweet-a-Toddy receives thousands of tweets per day
Tweets requesting home delivery
Tweets about quality of productsTweets related to enquirers
They requires following things to be automated
Identify tweet categoryProcess home-delivery requestEvaluate quality related tweets
How?
How to find a solution for Tweet-a-Toddy
Jaganadh G Practical Natural Language Processing
![Page 17: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/17.jpg)
Practical NLP
Problem
Tweet-a-Toddy receives thousands of tweets per day
Tweets requesting home deliveryTweets about quality of products
Tweets related to enquirers
They requires following things to be automated
Identify tweet categoryProcess home-delivery requestEvaluate quality related tweets
How?
How to find a solution for Tweet-a-Toddy
Jaganadh G Practical Natural Language Processing
![Page 18: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/18.jpg)
Practical NLP
Problem
Tweet-a-Toddy receives thousands of tweets per day
Tweets requesting home deliveryTweets about quality of productsTweets related to enquirers
They requires following things to be automated
Identify tweet categoryProcess home-delivery requestEvaluate quality related tweets
How?
How to find a solution for Tweet-a-Toddy
Jaganadh G Practical Natural Language Processing
![Page 19: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/19.jpg)
Practical NLP
Problem
Tweet-a-Toddy receives thousands of tweets per day
Tweets requesting home deliveryTweets about quality of productsTweets related to enquirers
They requires following things to be automated
Identify tweet categoryProcess home-delivery requestEvaluate quality related tweets
How?
How to find a solution for Tweet-a-Toddy
Jaganadh G Practical Natural Language Processing
![Page 20: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/20.jpg)
Practical NLP
Problem
Tweet-a-Toddy receives thousands of tweets per day
Tweets requesting home deliveryTweets about quality of productsTweets related to enquirers
They requires following things to be automated
Identify tweet category
Process home-delivery requestEvaluate quality related tweets
How?
How to find a solution for Tweet-a-Toddy
Jaganadh G Practical Natural Language Processing
![Page 21: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/21.jpg)
Practical NLP
Problem
Tweet-a-Toddy receives thousands of tweets per day
Tweets requesting home deliveryTweets about quality of productsTweets related to enquirers
They requires following things to be automated
Identify tweet categoryProcess home-delivery request
Evaluate quality related tweets
How?
How to find a solution for Tweet-a-Toddy
Jaganadh G Practical Natural Language Processing
![Page 22: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/22.jpg)
Practical NLP
Problem
Tweet-a-Toddy receives thousands of tweets per day
Tweets requesting home deliveryTweets about quality of productsTweets related to enquirers
They requires following things to be automated
Identify tweet categoryProcess home-delivery requestEvaluate quality related tweets
How?
How to find a solution for Tweet-a-Toddy
Jaganadh G Practical Natural Language Processing
![Page 23: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/23.jpg)
Practical NLP
Problem
Tweet-a-Toddy receives thousands of tweets per day
Tweets requesting home deliveryTweets about quality of productsTweets related to enquirers
They requires following things to be automated
Identify tweet categoryProcess home-delivery requestEvaluate quality related tweets
How?
How to find a solution for Tweet-a-Toddy
Jaganadh G Practical Natural Language Processing
![Page 24: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/24.jpg)
Solution
??
Any Solutions
Some thoughts
Text Classification
Entity Identification
Information Extraction
Sentiment Analysis
Parsing, gammer ...
Regex (Regular Expressions)
Jaganadh G Practical Natural Language Processing
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Solution
??
Any Solutions
Some thoughts
Text Classification
Entity Identification
Information Extraction
Sentiment Analysis
Parsing, gammer ...
Regex (Regular Expressions)
Jaganadh G Practical Natural Language Processing
![Page 26: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/26.jpg)
Solution
??
Any Solutions
Some thoughts
Text Classification
Entity Identification
Information Extraction
Sentiment Analysis
Parsing, gammer ...
Regex (Regular Expressions)
Jaganadh G Practical Natural Language Processing
![Page 27: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/27.jpg)
Solution
??
Any Solutions
Some thoughts
Text Classification
Entity Identification
Information Extraction
Sentiment Analysis
Parsing, gammer ...
Regex (Regular Expressions)
Jaganadh G Practical Natural Language Processing
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Solution
??
Any Solutions
Some thoughts
Text Classification
Entity Identification
Information Extraction
Sentiment Analysis
Parsing, gammer ...
Regex (Regular Expressions)
Jaganadh G Practical Natural Language Processing
![Page 29: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/29.jpg)
Solution
??
Any Solutions
Some thoughts
Text Classification
Entity Identification
Information Extraction
Sentiment Analysis
Parsing, gammer ...
Regex (Regular Expressions)
Jaganadh G Practical Natural Language Processing
![Page 30: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/30.jpg)
Solution
??
Any Solutions
Some thoughts
Text Classification
Entity Identification
Information Extraction
Sentiment Analysis
Parsing, gammer ...
Regex (Regular Expressions)
Jaganadh G Practical Natural Language Processing
![Page 31: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/31.jpg)
Solution
??
Any Solutions
Some thoughts
Text Classification
Entity Identification
Information Extraction
Sentiment Analysis
Parsing, gammer ...
Regex (Regular Expressions)
Jaganadh G Practical Natural Language Processing
![Page 32: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/32.jpg)
Another Practical Question
Everybody might have used spell checker available in wordprocessing systems like OpenOffice.org or Microsoft WordAny 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
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Another Practical Question
Everybody might have used spell checker available in wordprocessing systems like OpenOffice.org or Microsoft WordAny 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
![Page 34: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/34.jpg)
Another Practical Question
Everybody might have used spell checker available in wordprocessing systems like OpenOffice.org or Microsoft WordAny 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
![Page 35: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/35.jpg)
Another Practical Question
Everybody might have used spell checker available in wordprocessing systems like OpenOffice.org or Microsoft WordAny 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
![Page 36: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/36.jpg)
Another Practical Question ...
Context Sensitive Spell-checking
Identifying and suggesting spelling of words based on contextHow ??
Solutions
Statistical Models
Word category based suggestions
Jaganadh G Practical Natural Language Processing
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Another Practical Question ...
Context Sensitive Spell-checking
Identifying and suggesting spelling of words based on contextHow ??
Solutions
Statistical Models
Word category based suggestions
Jaganadh G Practical Natural Language Processing
![Page 38: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/38.jpg)
Another Practical Question ...
Context Sensitive Spell-checking
Identifying and suggesting spelling of words based on contextHow ??
Solutions
Statistical Models
Word category based suggestions
Jaganadh G Practical Natural Language Processing
![Page 39: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/39.jpg)
Another Practical Question ...
Context Sensitive Spell-checking
Identifying and suggesting spelling of words based on contextHow ??
Solutions
Statistical Models
Word category based suggestions
Jaganadh G Practical Natural Language Processing
![Page 40: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/40.jpg)
Can Machines Translate ??
Answer !!!
Jaganadh G Practical Natural Language Processing
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Why NLP ?
Because ”Information is Power !!!”
Every day wast amount of text and speech data is beingproduced
Internet == at least 40 Million pages
Picture Courtesy: http://soundsgood.in/wikipediafat print book/
Jaganadh G Practical Natural Language Processing
![Page 42: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/42.jpg)
Why NLP ?
Because ”Information is Power !!!”
Every day wast amount of text and speech data is beingproduced
Internet == at least 40 Million pages
Picture Courtesy: http://soundsgood.in/wikipediafat print book/
Jaganadh G Practical Natural Language Processing
![Page 43: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/43.jpg)
Why NLP ?
Because ”Information is Power !!!”
Every day wast amount of text and speech data is beingproduced
Internet == at least 40 Million pages
Picture Courtesy: http://soundsgood.in/wikipediafat print book/
Jaganadh G Practical Natural Language Processing
![Page 44: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/44.jpg)
Why NLP ?
Because ”Information is Power !!!”
Every day wast amount of text and speech data is beingproduced
Internet == at least 40 Million pages
Picture Courtesy: http://soundsgood.in/wikipediafat print book/
Jaganadh G Practical Natural Language Processing
![Page 45: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/45.jpg)
Why NLP ?
Because ”Information is Power !!!”
Every day wast amount of text and speech data is beingproduced
Internet == at least 40 Million pages
Picture Courtesy: http://soundsgood.in/wikipediafat print book/
Jaganadh G Practical Natural Language Processing
![Page 46: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/46.jpg)
History
Second World War !!!
Machine Translation
Now :
Most promising imperfect technology
Moves from Lab to Industry to Layman
Jaganadh G Practical Natural Language Processing
![Page 47: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/47.jpg)
History
Second World War !!!
Machine Translation
Now :
Most promising imperfect technology
Moves from Lab to Industry to Layman
Jaganadh G Practical Natural Language Processing
![Page 48: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/48.jpg)
History
Second World War !!!
Machine Translation
Now :
Most promising imperfect technology
Moves from Lab to Industry to Layman
Jaganadh G Practical Natural Language Processing
![Page 49: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/49.jpg)
History
Second World War !!!
Machine Translation
Now :
Most promising imperfect technology
Moves from Lab to Industry to Layman
Jaganadh G Practical Natural Language Processing
![Page 50: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/50.jpg)
History
Second World War !!!
Machine Translation
Now :
Most promising imperfect technology
Moves from Lab to Industry to Layman
Jaganadh G Practical Natural Language Processing
![Page 51: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/51.jpg)
History
Second World War !!!
Machine Translation
Now :
Most promising imperfect technology
Moves from Lab to Industry to Layman
Jaganadh G Practical Natural Language Processing
![Page 52: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/52.jpg)
NLP Really Hard to Achieve?
NLP delas with human languagesHuman Language is dynamic and mysterious !!!
Communication in Human Language
Jaganadh G Practical Natural Language Processing
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NLP Really Hard to Achieve?
NLP delas with human languagesHuman Language is dynamic and mysterious !!!
Communication in Human Language
Jaganadh G Practical Natural Language Processing
![Page 54: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/54.jpg)
NLP Really Hard to Achieve?
Levels of Knowledge encoding in Language Data
Jaganadh G Practical Natural Language Processing
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Tasks in NLP
Broad Areas
Text Processing
Speech Processing
Jaganadh G Practical Natural Language Processing
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Tasks in NLP
Broad Areas
Text Processing
Speech Processing
Jaganadh G Practical Natural Language Processing
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Tasks in NLP
Broad Areas
Text Processing
Speech Processing
Jaganadh G Practical Natural Language Processing
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Major tasks in Text Processing
Word Level Analysis
Morphological SynthesisPart of Speech TaggingStemmingLemmatization
Sentence Level Analysis - Syntactical Parsing
Discourse Analysis - Semantic Processing
Jaganadh G Practical Natural Language Processing
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Major tasks in Text Processing
Word Level Analysis
Morphological SynthesisPart of Speech TaggingStemmingLemmatization
Sentence Level Analysis - Syntactical Parsing
Discourse Analysis - Semantic Processing
Jaganadh G Practical Natural Language Processing
![Page 60: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/60.jpg)
Major tasks in Text Processing
Word Level Analysis
Morphological Synthesis
Part of Speech TaggingStemmingLemmatization
Sentence Level Analysis - Syntactical Parsing
Discourse Analysis - Semantic Processing
Jaganadh G Practical Natural Language Processing
![Page 61: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/61.jpg)
Major tasks in Text Processing
Word Level Analysis
Morphological SynthesisPart of Speech Tagging
StemmingLemmatization
Sentence Level Analysis - Syntactical Parsing
Discourse Analysis - Semantic Processing
Jaganadh G Practical Natural Language Processing
![Page 62: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/62.jpg)
Major tasks in Text Processing
Word Level Analysis
Morphological SynthesisPart of Speech TaggingStemming
Lemmatization
Sentence Level Analysis - Syntactical Parsing
Discourse Analysis - Semantic Processing
Jaganadh G Practical Natural Language Processing
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Major tasks in Text Processing
Word Level Analysis
Morphological SynthesisPart of Speech TaggingStemmingLemmatization
Sentence Level Analysis - Syntactical Parsing
Discourse Analysis - Semantic Processing
Jaganadh G Practical Natural Language Processing
![Page 64: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/64.jpg)
Major tasks in Text Processing
Word Level Analysis
Morphological SynthesisPart of Speech TaggingStemmingLemmatization
Sentence Level Analysis - Syntactical Parsing
Discourse Analysis - Semantic Processing
Jaganadh G Practical Natural Language Processing
![Page 65: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/65.jpg)
Major tasks in Text Processing
Word Level Analysis
Morphological SynthesisPart of Speech TaggingStemmingLemmatization
Sentence Level Analysis - Syntactical Parsing
Discourse Analysis - Semantic Processing
Jaganadh G Practical Natural Language Processing
![Page 66: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/66.jpg)
Morphology
The branch of linguistics that studies word structures.
To a computer program a word is : ???
Morphological analysis can be explained as: the process ofanalyzing words to identify its constituents
Computational Analysis of Morphology
Morphological Analysis
Morphological Generation
Stemming
Lemmatization
Jaganadh G Practical Natural Language Processing
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Morphology
The branch of linguistics that studies word structures.
To a computer program a word is : ???
Morphological analysis can be explained as: the process ofanalyzing words to identify its constituents
Computational Analysis of Morphology
Morphological Analysis
Morphological Generation
Stemming
Lemmatization
Jaganadh G Practical Natural Language Processing
![Page 68: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/68.jpg)
Morphology
The branch of linguistics that studies word structures.
To a computer program a word is : ???
Morphological analysis can be explained as: the process ofanalyzing words to identify its constituents
Computational Analysis of Morphology
Morphological Analysis
Morphological Generation
Stemming
Lemmatization
Jaganadh G Practical Natural Language Processing
![Page 69: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/69.jpg)
Morphology
The branch of linguistics that studies word structures.
To a computer program a word is : ???
Morphological analysis can be explained as: the process ofanalyzing words to identify its constituents
Computational Analysis of Morphology
Morphological Analysis
Morphological Generation
Stemming
Lemmatization
Jaganadh G Practical Natural Language Processing
![Page 70: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/70.jpg)
Morphology
The branch of linguistics that studies word structures.
To a computer program a word is : ???
Morphological analysis can be explained as: the process ofanalyzing words to identify its constituents
Computational Analysis of Morphology
Morphological Analysis
Morphological Generation
Stemming
Lemmatization
Jaganadh G Practical Natural Language Processing
![Page 71: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/71.jpg)
Morphology
The branch of linguistics that studies word structures.
To a computer program a word is : ???
Morphological analysis can be explained as: the process ofanalyzing words to identify its constituents
Computational Analysis of Morphology
Morphological Analysis
Morphological Generation
Stemming
Lemmatization
Jaganadh G Practical Natural Language Processing
![Page 72: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/72.jpg)
Morphology
The branch of linguistics that studies word structures.
To a computer program a word is : ???
Morphological analysis can be explained as: the process ofanalyzing words to identify its constituents
Computational Analysis of Morphology
Morphological Analysis
Morphological Generation
Stemming
Lemmatization
Jaganadh G Practical Natural Language Processing
![Page 73: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/73.jpg)
Morphology
The branch of linguistics that studies word structures.
To a computer program a word is : ???
Morphological analysis can be explained as: the process ofanalyzing words to identify its constituents
Computational Analysis of Morphology
Morphological Analysis
Morphological Generation
Stemming
Lemmatization
Jaganadh G Practical Natural Language Processing
![Page 74: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/74.jpg)
Practical Question from Morphology
Approximate number of word forms that can be derived from
the word”maram”
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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, basedon 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
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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, basedon 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
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Syntactical Parsing
Parsing
In computer science and linguistics, parsing, or, more formally,syntactic analysis, is the process of analyzing a text, made of asequence of tokens (for example, words), to determine itsgrammatical structure with respect to a given (more or less)formal grammar.
Sentences are ambiguous !!!!
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Syntactical Parsing
Parsing
In computer science and linguistics, parsing, or, more formally,syntactic analysis, is the process of analyzing a text, made of asequence of tokens (for example, words), to determine itsgrammatical structure with respect to a given (more or less)formal grammar.
Sentences are ambiguous !!!!
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Semantics
Study of meaning ans its structure
Word meaning is ambiguous !!!!E.g. marriage
Jaganadh G Practical Natural Language Processing
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Semantics
Study of meaning ans its structure
Word meaning is ambiguous !!!!E.g. marriage
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Where can I apply this techniques?
Machine Translation Systems
Search Engine
Spell-checker
Grammar Checker
..........
Jaganadh G Practical Natural Language Processing
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Where can I apply this techniques?
Machine Translation Systems
Search Engine
Spell-checker
Grammar Checker
..........
Jaganadh G Practical Natural Language Processing
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Where can I apply this techniques?
Machine Translation Systems
Search Engine
Spell-checker
Grammar Checker
..........
Jaganadh G Practical Natural Language Processing
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Where can I apply this techniques?
Machine Translation Systems
Search Engine
Spell-checker
Grammar Checker
..........
Jaganadh G Practical Natural Language Processing
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Where can I apply this techniques?
Machine Translation Systems
Search Engine
Spell-checker
Grammar Checker
..........
Jaganadh G Practical Natural Language Processing
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Other Interesting Tasks
Named Entity Identification
Information Extraction
Information Retrieval
Text Classification and Clustering
Jaganadh G Practical Natural Language Processing
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Other Interesting Tasks
Named Entity Identification
Information Extraction
Information Retrieval
Text Classification and Clustering
Jaganadh G Practical Natural Language Processing
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Other Interesting Tasks
Named Entity Identification
Information Extraction
Information Retrieval
Text Classification and Clustering
Jaganadh G Practical Natural Language Processing
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Other Interesting Tasks
Named Entity Identification
Information Extraction
Information Retrieval
Text Classification and Clustering
Jaganadh G Practical Natural Language Processing
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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
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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
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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
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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
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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
![Page 95: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/95.jpg)
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
![Page 96: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/96.jpg)
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
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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
![Page 98: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/98.jpg)
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
![Page 99: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/99.jpg)
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
![Page 100: Practical Natural Language Processing From Theory to Industrial Applications](https://reader033.vdocuments.us/reader033/viewer/2022061223/54c669b44a7959342b8b4621/html5/thumbnails/100.jpg)
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
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Future of NLP
Future!!!
Semantics oriented technologies
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NLP in other domains
Bio-Medical
Legal
Forensic Science
Advertisement
Education
Politics
E-governance
Business Development
Marketing
and where ever we use language !!!
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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
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Natural Language Processing in India
Industry
Microsoft
Yahoo!
AOL
365Media Pvt. Ltd.
Inside View
Thaazza
AIAIO Labs
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Questions ??
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References
Daniel Jurafsky,James H. Martin, SPEECH andLANGUAGE PROCESSING, 2nd Edition.
U.S. Tiwary, Tanveer Siddiqui , Natural LanguageProcessing and Information Retrieval
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Finally
Jaganadh G Practical Natural Language Processing
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Questions ??
Jaganadh G Practical Natural Language Processing
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References
Daniel Jurafsky,James H. Martin, SPEECH andLANGUAGE PROCESSING, 2nd Edition.
U.S. Tiwary, Tanveer Siddiqui , Natural LanguageProcessing and Information Retrieval
Jaganadh G Practical Natural Language Processing
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Finally
Jaganadh G Practical Natural Language Processing