SlideShare a Scribd company logo
1 of 11
Introduction to Web Mining
What is Web Mining? ,[object Object],[object Object],[object Object],[object Object],[object Object]
Web Mining ,[object Object],[object Object],[object Object]
Topics related to web mining ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Size of the Web ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The web as a graph ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Web graph ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Searching the Web Content consumers Content aggregators The Web
Two Approaches to Analyzing Data ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The future: Very Large-Scale Data Mining … Mem Disk CPU Mem Disk CPU Mem Disk CPU
Visit more self help tutorials ,[object Object],[object Object],[object Object]

More Related Content

What's hot (20)

A survey on web usage mining techniques
A survey on web usage mining techniquesA survey on web usage mining techniques
A survey on web usage mining techniques
 
Web Content Mining
Web Content MiningWeb Content Mining
Web Content Mining
 
Discovering knowledge using web structure mining
Discovering knowledge using web structure miningDiscovering knowledge using web structure mining
Discovering knowledge using web structure mining
 
Web mining
Web mining Web mining
Web mining
 
Web mining
Web miningWeb mining
Web mining
 
Web mining
Web miningWeb mining
Web mining
 
webmining overview
webmining overviewwebmining overview
webmining overview
 
Web content mining
Web content miningWeb content mining
Web content mining
 
Web Mining
Web MiningWeb Mining
Web Mining
 
Web mining
Web miningWeb mining
Web mining
 
Web mining
Web miningWeb mining
Web mining
 
5463 26 web mining
5463 26 web mining5463 26 web mining
5463 26 web mining
 
Web mining (structure mining)
Web mining (structure mining)Web mining (structure mining)
Web mining (structure mining)
 
A detail survey of page re ranking various web features and techniques
A detail survey of page re ranking various web features and techniquesA detail survey of page re ranking various web features and techniques
A detail survey of page re ranking various web features and techniques
 
Web mining
Web miningWeb mining
Web mining
 
Web Mining
Web MiningWeb Mining
Web Mining
 
Data Mining: Text and web mining
Data Mining: Text and web miningData Mining: Text and web mining
Data Mining: Text and web mining
 
Web mining
Web miningWeb mining
Web mining
 
Web mining
Web miningWeb mining
Web mining
 
Web mining
Web mining Web mining
Web mining
 

Viewers also liked

D2.3. Specification of Web Mining Process for Hypervideo Concept Identification
D2.3. Specification of Web Mining Process for Hypervideo Concept IdentificationD2.3. Specification of Web Mining Process for Hypervideo Concept Identification
D2.3. Specification of Web Mining Process for Hypervideo Concept IdentificationLinkedTV
 
Dotnet titles 2016 17
Dotnet titles 2016 17Dotnet titles 2016 17
Dotnet titles 2016 17praba123456
 
Taxonomies for E-commerce
Taxonomies for E-commerceTaxonomies for E-commerce
Taxonomies for E-commerceHeather Hedden
 
WEKA: Credibility Evaluating Whats Been Learned
WEKA: Credibility Evaluating Whats Been LearnedWEKA: Credibility Evaluating Whats Been Learned
WEKA: Credibility Evaluating Whats Been LearnedDataminingTools Inc
 
MS SQL SERVER: Microsoft naive bayes algorithm
MS SQL SERVER: Microsoft naive bayes algorithmMS SQL SERVER: Microsoft naive bayes algorithm
MS SQL SERVER: Microsoft naive bayes algorithmDataminingTools Inc
 
MS SQL SERVER: Programming sql server data mining
MS SQL SERVER: Programming sql server data miningMS SQL SERVER: Programming sql server data mining
MS SQL SERVER: Programming sql server data miningDataminingTools Inc
 
建築師法修正草案總說明
建築師法修正草案總說明建築師法修正草案總說明
建築師法修正草案總說明Filip Yang
 
Data Applied: Developer Quicklook
Data Applied: Developer QuicklookData Applied: Developer Quicklook
Data Applied: Developer QuicklookDataminingTools Inc
 
Bernoullis Random Variables And Binomial Distribution
Bernoullis Random Variables And Binomial DistributionBernoullis Random Variables And Binomial Distribution
Bernoullis Random Variables And Binomial DistributionDataminingTools Inc
 

Viewers also liked (18)

D2.3. Specification of Web Mining Process for Hypervideo Concept Identification
D2.3. Specification of Web Mining Process for Hypervideo Concept IdentificationD2.3. Specification of Web Mining Process for Hypervideo Concept Identification
D2.3. Specification of Web Mining Process for Hypervideo Concept Identification
 
Dotnet titles 2016 17
Dotnet titles 2016 17Dotnet titles 2016 17
Dotnet titles 2016 17
 
Taxonomies for E-commerce
Taxonomies for E-commerceTaxonomies for E-commerce
Taxonomies for E-commerce
 
WEKA: Credibility Evaluating Whats Been Learned
WEKA: Credibility Evaluating Whats Been LearnedWEKA: Credibility Evaluating Whats Been Learned
WEKA: Credibility Evaluating Whats Been Learned
 
MS SQL SERVER: Microsoft naive bayes algorithm
MS SQL SERVER: Microsoft naive bayes algorithmMS SQL SERVER: Microsoft naive bayes algorithm
MS SQL SERVER: Microsoft naive bayes algorithm
 
Ccc
CccCcc
Ccc
 
SQL Server: BI
SQL Server: BISQL Server: BI
SQL Server: BI
 
Oracle: DML
Oracle: DMLOracle: DML
Oracle: DML
 
MS SQL SERVER: Programming sql server data mining
MS SQL SERVER: Programming sql server data miningMS SQL SERVER: Programming sql server data mining
MS SQL SERVER: Programming sql server data mining
 
建築師法修正草案總說明
建築師法修正草案總說明建築師法修正草案總說明
建築師法修正草案總說明
 
Data Applied: Clustering
Data Applied: ClusteringData Applied: Clustering
Data Applied: Clustering
 
LISP: Type specifiers in lisp
LISP: Type specifiers in lispLISP: Type specifiers in lisp
LISP: Type specifiers in lisp
 
Mphone
MphoneMphone
Mphone
 
Data Applied: Developer Quicklook
Data Applied: Developer QuicklookData Applied: Developer Quicklook
Data Applied: Developer Quicklook
 
Bernoullis Random Variables And Binomial Distribution
Bernoullis Random Variables And Binomial DistributionBernoullis Random Variables And Binomial Distribution
Bernoullis Random Variables And Binomial Distribution
 
Txomin Hartz Txikia
Txomin Hartz TxikiaTxomin Hartz Txikia
Txomin Hartz Txikia
 
Data Applied:Tree Maps
Data Applied:Tree MapsData Applied:Tree Maps
Data Applied:Tree Maps
 
Quick Look At Classification
Quick Look At ClassificationQuick Look At Classification
Quick Look At Classification
 

Similar to Webmining Overview

Evolution Towards Web 3.0: The Semantic Web
Evolution Towards Web 3.0: The Semantic WebEvolution Towards Web 3.0: The Semantic Web
Evolution Towards Web 3.0: The Semantic WebLeeFeigenbaum
 
BAQMaR - Conference DM
BAQMaR - Conference DMBAQMaR - Conference DM
BAQMaR - Conference DMBAQMaR
 
Literature Survey on Web Mining
Literature Survey on Web MiningLiterature Survey on Web Mining
Literature Survey on Web MiningIOSR Journals
 
International conference On Computer Science And technology
International conference On Computer Science And technologyInternational conference On Computer Science And technology
International conference On Computer Science And technologyanchalsinghdm
 
Business Intelligence: A Rapidly Growing Option through Web Mining
Business Intelligence: A Rapidly Growing Option through Web  MiningBusiness Intelligence: A Rapidly Growing Option through Web  Mining
Business Intelligence: A Rapidly Growing Option through Web MiningIOSR Journals
 
A Study Web Data Mining Challenges And Application For Information Extraction
A Study  Web Data Mining Challenges And Application For Information ExtractionA Study  Web Data Mining Challenges And Application For Information Extraction
A Study Web Data Mining Challenges And Application For Information ExtractionScott Bou
 
Data preparation for mining world wide web browsing patterns (1999)
Data preparation for mining world wide web browsing patterns (1999)Data preparation for mining world wide web browsing patterns (1999)
Data preparation for mining world wide web browsing patterns (1999)OUM SAOKOSAL
 
Data Mining: Text and web mining
Data Mining: Text and web miningData Mining: Text and web mining
Data Mining: Text and web miningDatamining Tools
 
Internet Research: Finding Websites, Blogs, Wikis, and More
Internet Research: Finding Websites, Blogs, Wikis, and MoreInternet Research: Finding Websites, Blogs, Wikis, and More
Internet Research: Finding Websites, Blogs, Wikis, and Moreeclark131
 
RESEARCH ISSUES IN WEB MINING
RESEARCH ISSUES IN WEB MINING RESEARCH ISSUES IN WEB MINING
RESEARCH ISSUES IN WEB MINING ijcax
 
RESEARCH ISSUES IN WEB MINING
RESEARCH ISSUES IN WEB MINING RESEARCH ISSUES IN WEB MINING
RESEARCH ISSUES IN WEB MINING ijcax
 
RESEARCH ISSUES IN WEB MINING
RESEARCH ISSUES IN WEB MINING RESEARCH ISSUES IN WEB MINING
RESEARCH ISSUES IN WEB MINING ijcax
 
RESEARCH ISSUES IN WEB MINING
RESEARCH ISSUES IN WEB MINING RESEARCH ISSUES IN WEB MINING
RESEARCH ISSUES IN WEB MINING ijcax
 
RESEARCH ISSUES IN WEB MINING
RESEARCH ISSUES IN WEB MINING RESEARCH ISSUES IN WEB MINING
RESEARCH ISSUES IN WEB MINING ijcax
 

Similar to Webmining Overview (20)

Evolution Towards Web 3.0: The Semantic Web
Evolution Towards Web 3.0: The Semantic WebEvolution Towards Web 3.0: The Semantic Web
Evolution Towards Web 3.0: The Semantic Web
 
Web mining
Web miningWeb mining
Web mining
 
BAQMaR - Conference DM
BAQMaR - Conference DMBAQMaR - Conference DM
BAQMaR - Conference DM
 
Literature Survey on Web Mining
Literature Survey on Web MiningLiterature Survey on Web Mining
Literature Survey on Web Mining
 
web mining
web miningweb mining
web mining
 
International conference On Computer Science And technology
International conference On Computer Science And technologyInternational conference On Computer Science And technology
International conference On Computer Science And technology
 
search
searchsearch
search
 
search
searchsearch
search
 
Business Intelligence: A Rapidly Growing Option through Web Mining
Business Intelligence: A Rapidly Growing Option through Web  MiningBusiness Intelligence: A Rapidly Growing Option through Web  Mining
Business Intelligence: A Rapidly Growing Option through Web Mining
 
A Study Web Data Mining Challenges And Application For Information Extraction
A Study  Web Data Mining Challenges And Application For Information ExtractionA Study  Web Data Mining Challenges And Application For Information Extraction
A Study Web Data Mining Challenges And Application For Information Extraction
 
Data preparation for mining world wide web browsing patterns (1999)
Data preparation for mining world wide web browsing patterns (1999)Data preparation for mining world wide web browsing patterns (1999)
Data preparation for mining world wide web browsing patterns (1999)
 
WEB MINING.pptx
WEB MINING.pptxWEB MINING.pptx
WEB MINING.pptx
 
Data Mining: Text and web mining
Data Mining: Text and web miningData Mining: Text and web mining
Data Mining: Text and web mining
 
Web mining
Web miningWeb mining
Web mining
 
Internet Research: Finding Websites, Blogs, Wikis, and More
Internet Research: Finding Websites, Blogs, Wikis, and MoreInternet Research: Finding Websites, Blogs, Wikis, and More
Internet Research: Finding Websites, Blogs, Wikis, and More
 
RESEARCH ISSUES IN WEB MINING
RESEARCH ISSUES IN WEB MINING RESEARCH ISSUES IN WEB MINING
RESEARCH ISSUES IN WEB MINING
 
RESEARCH ISSUES IN WEB MINING
RESEARCH ISSUES IN WEB MINING RESEARCH ISSUES IN WEB MINING
RESEARCH ISSUES IN WEB MINING
 
RESEARCH ISSUES IN WEB MINING
RESEARCH ISSUES IN WEB MINING RESEARCH ISSUES IN WEB MINING
RESEARCH ISSUES IN WEB MINING
 
RESEARCH ISSUES IN WEB MINING
RESEARCH ISSUES IN WEB MINING RESEARCH ISSUES IN WEB MINING
RESEARCH ISSUES IN WEB MINING
 
RESEARCH ISSUES IN WEB MINING
RESEARCH ISSUES IN WEB MINING RESEARCH ISSUES IN WEB MINING
RESEARCH ISSUES IN WEB MINING
 

More from DataminingTools Inc

AI: Introduction to artificial intelligence
AI: Introduction to artificial intelligenceAI: Introduction to artificial intelligence
AI: Introduction to artificial intelligenceDataminingTools Inc
 
Data Mining: Mining stream time series and sequence data
Data Mining: Mining stream time series and sequence dataData Mining: Mining stream time series and sequence data
Data Mining: Mining stream time series and sequence dataDataminingTools Inc
 
Data Mining: Mining ,associations, and correlations
Data Mining: Mining ,associations, and correlationsData Mining: Mining ,associations, and correlations
Data Mining: Mining ,associations, and correlationsDataminingTools Inc
 
Data Mining: Graph mining and social network analysis
Data Mining: Graph mining and social network analysisData Mining: Graph mining and social network analysis
Data Mining: Graph mining and social network analysisDataminingTools Inc
 
Data warehouse and olap technology
Data warehouse and olap technologyData warehouse and olap technology
Data warehouse and olap technologyDataminingTools Inc
 
Data Mining: clustering and analysis
Data Mining: clustering and analysisData Mining: clustering and analysis
Data Mining: clustering and analysisDataminingTools Inc
 

More from DataminingTools Inc (20)

Terminology Machine Learning
Terminology Machine LearningTerminology Machine Learning
Terminology Machine Learning
 
Techniques Machine Learning
Techniques Machine LearningTechniques Machine Learning
Techniques Machine Learning
 
Machine learning Introduction
Machine learning IntroductionMachine learning Introduction
Machine learning Introduction
 
Areas of machine leanring
Areas of machine leanringAreas of machine leanring
Areas of machine leanring
 
AI: Planning and AI
AI: Planning and AIAI: Planning and AI
AI: Planning and AI
 
AI: Logic in AI 2
AI: Logic in AI 2AI: Logic in AI 2
AI: Logic in AI 2
 
AI: Logic in AI
AI: Logic in AIAI: Logic in AI
AI: Logic in AI
 
AI: Learning in AI 2
AI: Learning in AI 2AI: Learning in AI 2
AI: Learning in AI 2
 
AI: Learning in AI
AI: Learning in AI AI: Learning in AI
AI: Learning in AI
 
AI: Introduction to artificial intelligence
AI: Introduction to artificial intelligenceAI: Introduction to artificial intelligence
AI: Introduction to artificial intelligence
 
AI: Belief Networks
AI: Belief NetworksAI: Belief Networks
AI: Belief Networks
 
AI: AI & Searching
AI: AI & SearchingAI: AI & Searching
AI: AI & Searching
 
AI: AI & Problem Solving
AI: AI & Problem SolvingAI: AI & Problem Solving
AI: AI & Problem Solving
 
Data Mining: Outlier analysis
Data Mining: Outlier analysisData Mining: Outlier analysis
Data Mining: Outlier analysis
 
Data Mining: Mining stream time series and sequence data
Data Mining: Mining stream time series and sequence dataData Mining: Mining stream time series and sequence data
Data Mining: Mining stream time series and sequence data
 
Data Mining: Mining ,associations, and correlations
Data Mining: Mining ,associations, and correlationsData Mining: Mining ,associations, and correlations
Data Mining: Mining ,associations, and correlations
 
Data Mining: Graph mining and social network analysis
Data Mining: Graph mining and social network analysisData Mining: Graph mining and social network analysis
Data Mining: Graph mining and social network analysis
 
Data warehouse and olap technology
Data warehouse and olap technologyData warehouse and olap technology
Data warehouse and olap technology
 
Data Mining: Data processing
Data Mining: Data processingData Mining: Data processing
Data Mining: Data processing
 
Data Mining: clustering and analysis
Data Mining: clustering and analysisData Mining: clustering and analysis
Data Mining: clustering and analysis
 

Recently uploaded

Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Sapana Sha
 
Concept of Vouching. B.Com(Hons) /B.Compdf
Concept of Vouching. B.Com(Hons) /B.CompdfConcept of Vouching. B.Com(Hons) /B.Compdf
Concept of Vouching. B.Com(Hons) /B.CompdfUmakantAnnand
 
Crayon Activity Handout For the Crayon A
Crayon Activity Handout For the Crayon ACrayon Activity Handout For the Crayon A
Crayon Activity Handout For the Crayon AUnboundStockton
 
URLs and Routing in the Odoo 17 Website App
URLs and Routing in the Odoo 17 Website AppURLs and Routing in the Odoo 17 Website App
URLs and Routing in the Odoo 17 Website AppCeline George
 
Arihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdfArihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdfchloefrazer622
 
Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3JemimahLaneBuaron
 
Solving Puzzles Benefits Everyone (English).pptx
Solving Puzzles Benefits Everyone (English).pptxSolving Puzzles Benefits Everyone (English).pptx
Solving Puzzles Benefits Everyone (English).pptxOH TEIK BIN
 
MENTAL STATUS EXAMINATION format.docx
MENTAL     STATUS EXAMINATION format.docxMENTAL     STATUS EXAMINATION format.docx
MENTAL STATUS EXAMINATION format.docxPoojaSen20
 
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptxPOINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptxSayali Powar
 
The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13Steve Thomason
 
_Math 4-Q4 Week 5.pptx Steps in Collecting Data
_Math 4-Q4 Week 5.pptx Steps in Collecting Data_Math 4-Q4 Week 5.pptx Steps in Collecting Data
_Math 4-Q4 Week 5.pptx Steps in Collecting DataJhengPantaleon
 
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptxContemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptxRoyAbrique
 
Measures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeMeasures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeThiyagu K
 
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...Marc Dusseiller Dusjagr
 
APM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across SectorsAPM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across SectorsAssociation for Project Management
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)eniolaolutunde
 
Separation of Lanthanides/ Lanthanides and Actinides
Separation of Lanthanides/ Lanthanides and ActinidesSeparation of Lanthanides/ Lanthanides and Actinides
Separation of Lanthanides/ Lanthanides and ActinidesFatimaKhan178732
 
The basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptxThe basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptxheathfieldcps1
 

Recently uploaded (20)

Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
 
Concept of Vouching. B.Com(Hons) /B.Compdf
Concept of Vouching. B.Com(Hons) /B.CompdfConcept of Vouching. B.Com(Hons) /B.Compdf
Concept of Vouching. B.Com(Hons) /B.Compdf
 
Crayon Activity Handout For the Crayon A
Crayon Activity Handout For the Crayon ACrayon Activity Handout For the Crayon A
Crayon Activity Handout For the Crayon A
 
URLs and Routing in the Odoo 17 Website App
URLs and Routing in the Odoo 17 Website AppURLs and Routing in the Odoo 17 Website App
URLs and Routing in the Odoo 17 Website App
 
Arihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdfArihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdf
 
Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3
 
Solving Puzzles Benefits Everyone (English).pptx
Solving Puzzles Benefits Everyone (English).pptxSolving Puzzles Benefits Everyone (English).pptx
Solving Puzzles Benefits Everyone (English).pptx
 
Model Call Girl in Tilak Nagar Delhi reach out to us at 🔝9953056974🔝
Model Call Girl in Tilak Nagar Delhi reach out to us at 🔝9953056974🔝Model Call Girl in Tilak Nagar Delhi reach out to us at 🔝9953056974🔝
Model Call Girl in Tilak Nagar Delhi reach out to us at 🔝9953056974🔝
 
MENTAL STATUS EXAMINATION format.docx
MENTAL     STATUS EXAMINATION format.docxMENTAL     STATUS EXAMINATION format.docx
MENTAL STATUS EXAMINATION format.docx
 
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptxPOINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
 
The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13
 
_Math 4-Q4 Week 5.pptx Steps in Collecting Data
_Math 4-Q4 Week 5.pptx Steps in Collecting Data_Math 4-Q4 Week 5.pptx Steps in Collecting Data
_Math 4-Q4 Week 5.pptx Steps in Collecting Data
 
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptxContemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
 
Measures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeMeasures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and Mode
 
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
“Oh GOSH! Reflecting on Hackteria's Collaborative Practices in a Global Do-It...
 
APM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across SectorsAPM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across Sectors
 
Código Creativo y Arte de Software | Unidad 1
Código Creativo y Arte de Software | Unidad 1Código Creativo y Arte de Software | Unidad 1
Código Creativo y Arte de Software | Unidad 1
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)
 
Separation of Lanthanides/ Lanthanides and Actinides
Separation of Lanthanides/ Lanthanides and ActinidesSeparation of Lanthanides/ Lanthanides and Actinides
Separation of Lanthanides/ Lanthanides and Actinides
 
The basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptxThe basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptx
 

Webmining Overview

Editor's Notes

  1. Google’s usage logs are much bigger than their web crawl! Order of magnitude: terabytes per day No human in the loop
  2. Infinite number of pages because of dynamically generated content Lots of marketing hype around search engine index size claims