SlideShare una empresa de Scribd logo

Classification Of Web Documents

•Descargar como PPT, PDF•
•
H
hussainahmad77100

classification

Educación
1 de 34
Classification Chapter# 05 Data Mining The Web By Hussain Ahmad M.S (Semantic Web) University of Peshawar Pakistan
..Classification.. ,[object Object],[object Object],[object Object],[object Object]
..Classification.. ,[object Object],[object Object],[object Object]
..Classification.. ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
..Classification.. ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
..Classification.. ,[object Object],[object Object],[object Object]
Web Documents exhibit some specific properties ,[object Object],[object Object],[object Object],[object Object],[object Object]
Nearest-Neighbor Algorithm ,[object Object],[object Object],[object Object],[object Object]
..NN Algorithm.. ,[object Object],[object Object]
..NN Algorithm.. ,[object Object],[object Object],[object Object]
 
 
..NN Algorithm.. ,[object Object],[object Object],[object Object]
..NN Algorithm.. ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
..NN Algorithm.. ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
FEATURE SELECTION ,[object Object],[object Object],[object Object]
Naive Bayes Algorithm ,[object Object],[object Object],[object Object],[object Object],[object Object]
 
..Naive Bayes Algorithm.. ,[object Object],[object Object],[object Object],[object Object]
..Naive Bayes Algorithm.. ,[object Object]
..Naive Bayes Algorithm.. ,[object Object],[object Object],[object Object]
..Naive Bayes Algorithm.. ,[object Object],[object Object],[object Object],[object Object],[object Object]
..Naive Bayes Algorithm.. ,[object Object],[object Object],[object Object],[object Object],[object Object]
..Naive Bayes Algorithm.. ,[object Object],[object Object]
 
..Naive Bayes Algorithm.. ,[object Object],[object Object],[object Object],[object Object],[object Object]
..Naive Bayes Algorithm.. ,[object Object],[object Object],[object Object]
..Naive Bayes Algorithm.. ,[object Object],[object Object],[object Object],[object Object],[object Object],P(A | Theatre) ≈ 0.0000354208 and P(B | Theatre) ≈ 0.00000476511,
Numerical Approaches ,[object Object],[object Object],[object Object],[object Object]
..Numerical Approaches.. ,[object Object],[object Object],[object Object]
..Numerical Approaches.. ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
..Numerical Approaches.. ,[object Object],[object Object],[object Object]
RELATIONAL LEARNING ,[object Object],[object Object],[object Object],[object Object],[object Object]
..RELATIONAL LEARNING.. ,[object Object],[object Object],[object Object],[object Object]

Recomendados

Binary tree traversal ppt - 02.03.2020
Binary tree traversal ppt - 02.03.2020Binary tree traversal ppt - 02.03.2020
Binary tree traversal ppt - 02.03.2020V.V.Vanniapermal College for Women
 
b+ tree
b+ treeb+ tree
b+ treebitistu
 
Error Checking and Correction (Parity Bit, Majority Voting, Check Digit)
Error Checking and Correction (Parity Bit, Majority Voting, Check Digit)Error Checking and Correction (Parity Bit, Majority Voting, Check Digit)
Error Checking and Correction (Parity Bit, Majority Voting, Check Digit)Project Student
 
Indexing and-hashing
Indexing and-hashingIndexing and-hashing
Indexing and-hashingAmi Ranjit
 
B and B+ tree
B and B+ treeB and B+ tree
B and B+ treeAshish Arun
 
Data Cleaning Techniques
Data Cleaning TechniquesData Cleaning Techniques
Data Cleaning TechniquesAmir Masoud Sefidian
 
Linked List
Linked ListLinked List
Linked ListCHANDAN KUMAR
 
Computer Architecture - Data Path & Pipeline Hazards
Computer Architecture - Data Path & Pipeline HazardsComputer Architecture - Data Path & Pipeline Hazards
Computer Architecture - Data Path & Pipeline HazardsThyagharajan K.K.
 

Recomendados

Binary tree traversal ppt - 02.03.2020
Binary tree traversal ppt - 02.03.2020Binary tree traversal ppt - 02.03.2020
Binary tree traversal ppt - 02.03.2020V.V.Vanniapermal College for Women
 
b+ tree
b+ treeb+ tree
b+ treebitistu
 
Error Checking and Correction (Parity Bit, Majority Voting, Check Digit)
Error Checking and Correction (Parity Bit, Majority Voting, Check Digit)Error Checking and Correction (Parity Bit, Majority Voting, Check Digit)
Error Checking and Correction (Parity Bit, Majority Voting, Check Digit)Project Student
 
Indexing and-hashing
Indexing and-hashingIndexing and-hashing
Indexing and-hashingAmi Ranjit
 
B and B+ tree
B and B+ treeB and B+ tree
B and B+ treeAshish Arun
 
Data Cleaning Techniques
Data Cleaning TechniquesData Cleaning Techniques
Data Cleaning TechniquesAmir Masoud Sefidian
 
Linked List
Linked ListLinked List
Linked ListCHANDAN KUMAR
 
Computer Architecture - Data Path & Pipeline Hazards
Computer Architecture - Data Path & Pipeline HazardsComputer Architecture - Data Path & Pipeline Hazards
Computer Architecture - Data Path & Pipeline HazardsThyagharajan K.K.
 
Discretization and concept hierarchy(os)
Discretization and concept hierarchy(os)Discretization and concept hierarchy(os)
Discretization and concept hierarchy(os)snegacmr
 
Sorting ppt
Sorting pptSorting ppt
Sorting pptHassan Mustafa
 
Similarity Measures (pptx)
Similarity Measures (pptx)Similarity Measures (pptx)
Similarity Measures (pptx)JackDi2
 
Tree and graph
Tree and graphTree and graph
Tree and graphMuhaiminul Islam
 
Data Mining: Classification and analysis
Data Mining: Classification and analysisData Mining: Classification and analysis
Data Mining: Classification and analysisDataminingTools Inc
 
3.7 outlier analysis
3.7 outlier analysis3.7 outlier analysis
3.7 outlier analysisKrish_ver2
 
Dbms Notes Lecture 9 : Specialization, Generalization and Aggregation
Dbms Notes Lecture 9 : Specialization, Generalization and AggregationDbms Notes Lecture 9 : Specialization, Generalization and Aggregation
Dbms Notes Lecture 9 : Specialization, Generalization and AggregationBIT Durg
 
Data science.chapter-1,2,3
Data science.chapter-1,2,3Data science.chapter-1,2,3
Data science.chapter-1,2,3varshakumar21
 
Query Processing and Optimisation - Lecture 10 - Introduction to Databases (1...
Query Processing and Optimisation - Lecture 10 - Introduction to Databases (1...Query Processing and Optimisation - Lecture 10 - Introduction to Databases (1...
Query Processing and Optimisation - Lecture 10 - Introduction to Databases (1...Beat Signer
 
Depth first search [dfs]
Depth first search [dfs]Depth first search [dfs]
Depth first search [dfs]DEEPIKA T
 
Binary search tree in data structures
Binary search tree in data structuresBinary search tree in data structures
Binary search tree in data structureschauhankapil
 
Indexing Data Structure
Indexing Data StructureIndexing Data Structure
Indexing Data StructureVivek Kantariya
 
File Types in Data Structure
File Types in Data StructureFile Types in Data Structure
File Types in Data StructureProf Ansari
 
Semantic analysis
Semantic analysisSemantic analysis
Semantic analysisLahore Garrison University
 
Mass Storage Structure
Mass Storage StructureMass Storage Structure
Mass Storage StructureVimalanathan D
 
Internet Of Things (Question Paper) [October – 2018 | Choice Based Syllabus]
Internet Of Things (Question Paper) [October – 2018 | Choice Based Syllabus]Internet Of Things (Question Paper) [October – 2018 | Choice Based Syllabus]
Internet Of Things (Question Paper) [October – 2018 | Choice Based Syllabus]Mumbai B.Sc.IT Study
 
Computer organization & architecture chapter-1
Computer organization & architecture chapter-1Computer organization & architecture chapter-1
Computer organization & architecture chapter-1Shah Rukh Rayaz
 
Infix prefix postfix
Infix prefix postfixInfix prefix postfix
Infix prefix postfixSelf-Employed
 
1.8 discretization
1.8 discretization1.8 discretization
1.8 discretizationKrish_ver2
 
Query processing and Query Optimization
Query processing and Query OptimizationQuery processing and Query Optimization
Query processing and Query OptimizationNiraj Gandha
 
Data.Mining.C.6(II).classification and prediction
Data.Mining.C.6(II).classification and predictionData.Mining.C.6(II).classification and prediction
Data.Mining.C.6(II).classification and predictionMargaret Wang
 
Learning to Rank - From pairwise approach to listwise
Learning to Rank - From pairwise approach to listwiseLearning to Rank - From pairwise approach to listwise
Learning to Rank - From pairwise approach to listwiseHasan H Topcu
 

Más contenido relacionado

La actualidad más candente

Discretization and concept hierarchy(os)
Discretization and concept hierarchy(os)Discretization and concept hierarchy(os)
Discretization and concept hierarchy(os)snegacmr
 
Similarity Measures (pptx)
Similarity Measures (pptx)Similarity Measures (pptx)
Similarity Measures (pptx)JackDi2
 
Data Mining: Classification and analysis
Data Mining: Classification and analysisData Mining: Classification and analysis
Data Mining: Classification and analysisDataminingTools Inc
 
3.7 outlier analysis
3.7 outlier analysis3.7 outlier analysis
3.7 outlier analysisKrish_ver2
 
Dbms Notes Lecture 9 : Specialization, Generalization and Aggregation
Dbms Notes Lecture 9 : Specialization, Generalization and AggregationDbms Notes Lecture 9 : Specialization, Generalization and Aggregation
Dbms Notes Lecture 9 : Specialization, Generalization and AggregationBIT Durg
 
Data science.chapter-1,2,3
Data science.chapter-1,2,3Data science.chapter-1,2,3
Data science.chapter-1,2,3varshakumar21
 
Query Processing and Optimisation - Lecture 10 - Introduction to Databases (1...
Query Processing and Optimisation - Lecture 10 - Introduction to Databases (1...Query Processing and Optimisation - Lecture 10 - Introduction to Databases (1...
Query Processing and Optimisation - Lecture 10 - Introduction to Databases (1...Beat Signer
 
Depth first search [dfs]
Depth first search [dfs]Depth first search [dfs]
Depth first search [dfs]DEEPIKA T
 
Binary search tree in data structures
Binary search tree in data structuresBinary search tree in data structures
Binary search tree in data structureschauhankapil
 
File Types in Data Structure
File Types in Data StructureFile Types in Data Structure
File Types in Data StructureProf Ansari
 
Mass Storage Structure
Mass Storage StructureMass Storage Structure
Mass Storage StructureVimalanathan D
 
Internet Of Things (Question Paper) [October – 2018 | Choice Based Syllabus]
Internet Of Things (Question Paper) [October – 2018 | Choice Based Syllabus]Internet Of Things (Question Paper) [October – 2018 | Choice Based Syllabus]
Internet Of Things (Question Paper) [October – 2018 | Choice Based Syllabus]Mumbai B.Sc.IT Study
 
Computer organization & architecture chapter-1
Computer organization & architecture chapter-1Computer organization & architecture chapter-1
Computer organization & architecture chapter-1Shah Rukh Rayaz
 
Infix prefix postfix
Infix prefix postfixInfix prefix postfix
Infix prefix postfixSelf-Employed
 
1.8 discretization
1.8 discretization1.8 discretization
1.8 discretizationKrish_ver2
 
Query processing and Query Optimization
Query processing and Query OptimizationQuery processing and Query Optimization
Query processing and Query OptimizationNiraj Gandha
 

La actualidad más candente (20)

Discretization and concept hierarchy(os)
Discretization and concept hierarchy(os)Discretization and concept hierarchy(os)
Discretization and concept hierarchy(os)
 
Sorting ppt
Sorting pptSorting ppt
Sorting ppt
 
Similarity Measures (pptx)
Similarity Measures (pptx)Similarity Measures (pptx)
Similarity Measures (pptx)
 
Tree and graph
Tree and graphTree and graph
Tree and graph
 
Data Mining: Classification and analysis
Data Mining: Classification and analysisData Mining: Classification and analysis
Data Mining: Classification and analysis
 
3.7 outlier analysis
3.7 outlier analysis3.7 outlier analysis
3.7 outlier analysis
 
Dbms Notes Lecture 9 : Specialization, Generalization and Aggregation
Dbms Notes Lecture 9 : Specialization, Generalization and AggregationDbms Notes Lecture 9 : Specialization, Generalization and Aggregation
Dbms Notes Lecture 9 : Specialization, Generalization and Aggregation
 
Data science.chapter-1,2,3
Data science.chapter-1,2,3Data science.chapter-1,2,3
Data science.chapter-1,2,3
 
Query Processing and Optimisation - Lecture 10 - Introduction to Databases (1...
Query Processing and Optimisation - Lecture 10 - Introduction to Databases (1...Query Processing and Optimisation - Lecture 10 - Introduction to Databases (1...
Query Processing and Optimisation - Lecture 10 - Introduction to Databases (1...
 
Depth first search [dfs]
Depth first search [dfs]Depth first search [dfs]
Depth first search [dfs]
 
Binary search tree in data structures
Binary search tree in data structuresBinary search tree in data structures
Binary search tree in data structures
 
Indexing Data Structure
Indexing Data StructureIndexing Data Structure
Indexing Data Structure
 
File Types in Data Structure
File Types in Data StructureFile Types in Data Structure
File Types in Data Structure
 
Semantic analysis
Semantic analysisSemantic analysis
Semantic analysis
 
Mass Storage Structure
Mass Storage StructureMass Storage Structure
Mass Storage Structure
 
Internet Of Things (Question Paper) [October – 2018 | Choice Based Syllabus]
Internet Of Things (Question Paper) [October – 2018 | Choice Based Syllabus]Internet Of Things (Question Paper) [October – 2018 | Choice Based Syllabus]
Internet Of Things (Question Paper) [October – 2018 | Choice Based Syllabus]
 
Computer organization & architecture chapter-1
Computer organization & architecture chapter-1Computer organization & architecture chapter-1
Computer organization & architecture chapter-1
 
Infix prefix postfix
Infix prefix postfixInfix prefix postfix
Infix prefix postfix
 
1.8 discretization
1.8 discretization1.8 discretization
1.8 discretization
 
Query processing and Query Optimization
Query processing and Query OptimizationQuery processing and Query Optimization
Query processing and Query Optimization
 

Similar a Classification Of Web Documents

Data.Mining.C.6(II).classification and prediction
Data.Mining.C.6(II).classification and predictionData.Mining.C.6(II).classification and prediction
Data.Mining.C.6(II).classification and predictionMargaret Wang
 
Learning to Rank - From pairwise approach to listwise
Learning to Rank - From pairwise approach to listwiseLearning to Rank - From pairwise approach to listwise
Learning to Rank - From pairwise approach to listwiseHasan H Topcu
 
Machine learning and Neural Networks
Machine learning and Neural NetworksMachine learning and Neural Networks
Machine learning and Neural Networksbutest
 
Machine Learning and Artificial Neural Networks.ppt
Machine Learning and Artificial Neural Networks.pptMachine Learning and Artificial Neural Networks.ppt
Machine Learning and Artificial Neural Networks.pptAnshika865276
 
20070702 Text Categorization
20070702 Text Categorization20070702 Text Categorization
20070702 Text Categorizationmidi
 
Lecture 2
Lecture 2Lecture 2
Lecture 2butest
 
Textmining Predictive Models
Textmining Predictive ModelsTextmining Predictive Models
Textmining Predictive ModelsDatamining Tools
 
Textmining Predictive Models
Textmining Predictive ModelsTextmining Predictive Models
Textmining Predictive Modelsguest0edcaf
 
[系列活動] Machine Learning 機器學習課程
[系列活動] Machine Learning 機器學習課程[系列活動] Machine Learning 機器學習課程
[系列活動] Machine Learning 機器學習課程台灣資料科學年會
 
Textmining Retrieval And Clustering
Textmining Retrieval And ClusteringTextmining Retrieval And Clustering
Textmining Retrieval And ClusteringDataminingTools Inc
 
Textmining Retrieval And Clustering
Textmining Retrieval And ClusteringTextmining Retrieval And Clustering
Textmining Retrieval And Clusteringguest0edcaf
 
Textmining Retrieval And Clustering
Textmining Retrieval And ClusteringTextmining Retrieval And Clustering
Textmining Retrieval And ClusteringDatamining Tools
 

Similar a Classification Of Web Documents (20)

Data.Mining.C.6(II).classification and prediction
Data.Mining.C.6(II).classification and predictionData.Mining.C.6(II).classification and prediction
Data.Mining.C.6(II).classification and prediction
 
Learning to Rank - From pairwise approach to listwise
Learning to Rank - From pairwise approach to listwiseLearning to Rank - From pairwise approach to listwise
Learning to Rank - From pairwise approach to listwise
 
ppt
pptppt
ppt
 
nnml.ppt
nnml.pptnnml.ppt
nnml.ppt
 
Machine learning and Neural Networks
Machine learning and Neural NetworksMachine learning and Neural Networks
Machine learning and Neural Networks
 
Classification Continued
Classification ContinuedClassification Continued
Classification Continued
 
Classification Continued
Classification ContinuedClassification Continued
Classification Continued
 
Machine Learning and Artificial Neural Networks.ppt
Machine Learning and Artificial Neural Networks.pptMachine Learning and Artificial Neural Networks.ppt
Machine Learning and Artificial Neural Networks.ppt
 
20070702 Text Categorization
20070702 Text Categorization20070702 Text Categorization
20070702 Text Categorization
 
Lecture 2
Lecture 2Lecture 2
Lecture 2
 
TEXT CLUSTERING.doc
TEXT CLUSTERING.docTEXT CLUSTERING.doc
TEXT CLUSTERING.doc
 
Textmining Predictive Models
Textmining Predictive ModelsTextmining Predictive Models
Textmining Predictive Models
 
Textmining Predictive Models
Textmining Predictive ModelsTextmining Predictive Models
Textmining Predictive Models
 
Textmining Predictive Models
Textmining Predictive ModelsTextmining Predictive Models
Textmining Predictive Models
 
Supervised algorithms
Supervised algorithmsSupervised algorithms
Supervised algorithms
 
[系列活動] Machine Learning 機器學習課程
[系列活動] Machine Learning 機器學習課程[系列活動] Machine Learning 機器學習課程
[系列活動] Machine Learning 機器學習課程
 
python.pptx
python.pptxpython.pptx
python.pptx
 
Textmining Retrieval And Clustering
Textmining Retrieval And ClusteringTextmining Retrieval And Clustering
Textmining Retrieval And Clustering
 
Textmining Retrieval And Clustering
Textmining Retrieval And ClusteringTextmining Retrieval And Clustering
Textmining Retrieval And Clustering
 
Textmining Retrieval And Clustering
Textmining Retrieval And ClusteringTextmining Retrieval And Clustering
Textmining Retrieval And Clustering
 

Último

Application orientated numerical on hev.ppt
Application orientated numerical on hev.pptApplication orientated numerical on hev.ppt
Application orientated numerical on hev.pptRamjanShidvankar
 
General Principles of Intellectual Property: Concepts of Intellectual Proper...
General Principles of Intellectual Property: Concepts of Intellectual Proper...General Principles of Intellectual Property: Concepts of Intellectual Proper...
General Principles of Intellectual Property: Concepts of Intellectual Proper...Poonam Aher Patil
 
This PowerPoint helps students to consider the concept of infinity.
This PowerPoint helps students to consider the concept of infinity.This PowerPoint helps students to consider the concept of infinity.
This PowerPoint helps students to consider the concept of infinity.christianmathematics
 
Energy Resources. ( B. Pharmacy, 1st Year, Sem-II) Natural Resources
Energy Resources. ( B. Pharmacy, 1st Year, Sem-II) Natural ResourcesEnergy Resources. ( B. Pharmacy, 1st Year, Sem-II) Natural Resources
Energy Resources. ( B. Pharmacy, 1st Year, Sem-II) Natural ResourcesShubhangi Sonawane
 
ComPTIA Overview | Comptia Security+ Book SY0-701
ComPTIA Overview | Comptia Security+ Book SY0-701ComPTIA Overview | Comptia Security+ Book SY0-701
ComPTIA Overview | Comptia Security+ Book SY0-701bronxfugly43
 
Measures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SDMeasures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SDThiyagu K
 
Introduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsIntroduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsTechSoup
 
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
 
How to Give a Domain for a Field in Odoo 17
How to Give a Domain for a Field in Odoo 17How to Give a Domain for a Field in Odoo 17
How to Give a Domain for a Field in Odoo 17Celine George
 
microwave assisted reaction. General introduction
microwave assisted reaction. General introductionmicrowave assisted reaction. General introduction
microwave assisted reaction. General introductionMaksud Ahmed
 
ICT Role in 21st Century Education & its Challenges.pptx
ICT Role in 21st Century Education & its Challenges.pptxICT Role in 21st Century Education & its Challenges.pptx
ICT Role in 21st Century Education & its Challenges.pptxAreebaZafar22
 
Holdier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfHoldier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfagholdier
 
ICT role in 21st century education and it's challenges.
ICT role in 21st century education and it's challenges.ICT role in 21st century education and it's challenges.
ICT role in 21st century education and it's challenges.MaryamAhmad92
 
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...christianmathematics
 
The basics of sentences session 3pptx.pptx
The basics of sentences session 3pptx.pptxThe basics of sentences session 3pptx.pptx
The basics of sentences session 3pptx.pptxheathfieldcps1
 
Grant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy ConsultingGrant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy ConsultingTechSoup
 
Activity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfActivity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfciinovamais
 
On National Teacher Day, meet the 2024-25 Kenan Fellows
On National Teacher Day, meet the 2024-25 Kenan FellowsOn National Teacher Day, meet the 2024-25 Kenan Fellows
On National Teacher Day, meet the 2024-25 Kenan FellowsMebane Rash
 
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
 

Último (20)

Application orientated numerical on hev.ppt
Application orientated numerical on hev.pptApplication orientated numerical on hev.ppt
Application orientated numerical on hev.ppt
 
General Principles of Intellectual Property: Concepts of Intellectual Proper...
General Principles of Intellectual Property: Concepts of Intellectual Proper...General Principles of Intellectual Property: Concepts of Intellectual Proper...
General Principles of Intellectual Property: Concepts of Intellectual Proper...
 
This PowerPoint helps students to consider the concept of infinity.
This PowerPoint helps students to consider the concept of infinity.This PowerPoint helps students to consider the concept of infinity.
This PowerPoint helps students to consider the concept of infinity.
 
Energy Resources. ( B. Pharmacy, 1st Year, Sem-II) Natural Resources
Energy Resources. ( B. Pharmacy, 1st Year, Sem-II) Natural ResourcesEnergy Resources. ( B. Pharmacy, 1st Year, Sem-II) Natural Resources
Energy Resources. ( B. Pharmacy, 1st Year, Sem-II) Natural Resources
 
ComPTIA Overview | Comptia Security+ Book SY0-701
ComPTIA Overview | Comptia Security+ Book SY0-701ComPTIA Overview | Comptia Security+ Book SY0-701
ComPTIA Overview | Comptia Security+ Book SY0-701
 
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptxINDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
 
Measures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SDMeasures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SD
 
Introduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsIntroduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The Basics
 
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
 
How to Give a Domain for a Field in Odoo 17
How to Give a Domain for a Field in Odoo 17How to Give a Domain for a Field in Odoo 17
How to Give a Domain for a Field in Odoo 17
 
microwave assisted reaction. General introduction
microwave assisted reaction. General introductionmicrowave assisted reaction. General introduction
microwave assisted reaction. General introduction
 
ICT Role in 21st Century Education & its Challenges.pptx
ICT Role in 21st Century Education & its Challenges.pptxICT Role in 21st Century Education & its Challenges.pptx
ICT Role in 21st Century Education & its Challenges.pptx
 
Holdier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfHoldier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdf
 
ICT role in 21st century education and it's challenges.
ICT role in 21st century education and it's challenges.ICT role in 21st century education and it's challenges.
ICT role in 21st century education and it's challenges.
 
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
 
The basics of sentences session 3pptx.pptx
The basics of sentences session 3pptx.pptxThe basics of sentences session 3pptx.pptx
The basics of sentences session 3pptx.pptx
 
Grant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy ConsultingGrant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy Consulting
 
Activity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfActivity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdf
 
On National Teacher Day, meet the 2024-25 Kenan Fellows
On National Teacher Day, meet the 2024-25 Kenan FellowsOn National Teacher Day, meet the 2024-25 Kenan Fellows
On National Teacher Day, meet the 2024-25 Kenan Fellows
 
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
 

Classification Of Web Documents

  • 1. Classification Chapter# 05 Data Mining The Web By Hussain Ahmad M.S (Semantic Web) University of Peshawar Pakistan
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11.  
  • 12.  
  • 13.
  • 14.
  • 15.
  • 16.
  • 17.
  • 18.  
  • 19.
  • 20.
  • 21.
  • 22.
  • 23.
  • 24.
  • 25.  
  • 26.
  • 27.
  • 28.
  • 29.
  • 30.
  • 31.
  • 32.
  • 33.
  • 34.