SlideShare a Scribd company logo
1 of 43
Ms. Poonam Sinai Kenkre

 Why  is web crawler required?
 How does web crawler work?
 Crawling strategies
        Breadth first search traversal
        depth first search traversal
 Architecture of web crawler
 Crawling policies
 Distributed crawling
   The process or program used by search engines to
    download pages from the web for later processing by a
    search engine that will index the downloaded pages to
    provide fast searches.

   A program or automated script which browses the World
    Wide Web in a methodical, automated manner

   also known as web spiders and web robots.

   less used names- ants, bots and worms.
 What   is a web crawler?

 How   does web crawler work?
 Crawling strategies
       Breadth first search traversal
        depth first search traversal
 Architecture of web crawler
 Crawling policies
 Distributed crawling
Internet has a
wide expanse of
Information.
 Finding
relevant
information
requires an
efficient
mechanism.
Web Crawlers
provide that
scope to the
search engine.
 What   is a web crawler?
 Why  is web crawler required?
 How does web crawler work?
 Crawling strategies
       Breadth first search traversal
        depth first search traversal
 Architecture of web crawler
 Crawling policies
 Distributed crawling
 It starts with a list of URLs to visit, called the
  seeds . As the crawler visits these URLs, it
  identifies all the hyperlinks in the page and adds
  them to the list of visited URLs, called the crawl
  frontier
 URLs from the frontier are recursively visited
  according to a set of policies.
New url’s can be
specified here. This is
google’s web Crawler.
Initialize queue (Q) with initial set of known URL’s.
Until Q empty or page or time limit exhausted:
 Pop URL, L, from front of Q.
 If L is not an HTML page (.gif, .jpeg, .ps, .pdf, .ppt…)
       exit loop.
 If already visited L, continue loop(get next url).
 Download page, P, for L.
 If cannot download P (e.g. 404 error, robot excluded)
       exit loop, else.
 Index P (e.g. add to inverted index or store cached copy).
 Parse P to obtain list of new links N.
 Append N to the end of Q.
 What   is a web crawler?
 Why  is web crawler required?
 How does web crawler work?
 Crawling strategies
       Breadth first search traversal
        depth first search traversal
 Architecture of web crawler
 Crawling policies
 Distributed crawling
Alternate way of looking at the problem.

 Web is a huge directed graph, with
 documents as vertices and hyperlinks as
 edges.
 Need to explore the graph using a suitable
  graph traversal algorithm.
 W.r.t. previous ex: nodes are represented
 by rectangles and directed edges are
 drawn as arrows.
Given any graph and a set of seeds at which to start, the
  graph can be traversed using the algorithm

1. Put all the given seeds into the queue;
2. Prepare to keep a list of “visited” nodes (initially
   empty);
3. As long as the queue is not empty:
     a. Remove the first node from the queue;
     b. Append that node to the list of “visited” nodes
     c. For each edge starting at that node:
 i. If the node at the end of the edge already appears on
   the list of “visited” nodes or it is already in the queue,
   then do nothing more with that edge;
 ii. Otherwise, append the node at the end of the edge
   to the end of the queue.
 What   is a web crawler?
 Why  is web crawler required?
 How does web crawler work?
 Crawling strategies
        Breadth first search traversal
        Depth first search traversal
 Architecture of web crawler
 Crawling policies
 Parallel crawling
Use depth first search (DFS) algorithm
•   Get the 1st link not visited from the start
    page
•   Visit link and get 1st non-visited link
•   Repeat above step till no non-visited links
•   Go to next non-visited link in the previous
    level and repeat 2nd step
   depth-first goes off into one branch until it
    reaches a leaf node
        not good if the goal node is on another branch
        neither complete nor optimal
        uses much less space than breadth-first
            much fewer visited nodes to keep track of
            smaller fringe


   breadth-first is more careful by checking all
    alternatives
        complete and optimal
        very memory-intensive
 What   is a web crawler?
 Why  is web crawler required?
 How does web crawler work?
 Crawling strategies
        Breadth first search traversal
        Depth first search traversal
 Architecture of web crawler
 Crawling policies
 Distributed crawling
Doc            Robots      URL
                      Fingerprint    templates   set



       DNS


                                                 Dup
                       Content        URL
              Parse                              URL
www                    Seen?          Filter
                                                 Elim
      Fetch




                            URL Frontier
 URL Frontier: containing URLs yet to be fetches
  in the current crawl. At first, a seed set is stored
  in URL Frontier, and a crawler begins by taking a
  URL from the seed set.
 DNS: domain name service resolution. Look up IP
  address for domain names.
 Fetch: generally use the http protocol to fetch
  the URL.
 Parse: the page is parsed. Texts (images, videos,
  and etc.) and Links are extracted.
 Content    Seen?: test whether a web page
    with the same content has already been seen
    at another URL. Need to develop a way to
    measure the fingerprint of a web page.
   URL Filter:
     Whether the extracted URL should be excluded
      from the frontier (robots.txt).
     URL should be normalized (relative encoding).
       en.wikipedia.org/wiki/Main_Page
       <a href="/wiki/Wikipedia:General_disclaimer"
        title="Wikipedia:General
        disclaimer">Disclaimers</a>
   Dup URL Elim: the URL is checked for duplicate
    elimination.
 What   is a web crawler?
 Why  is web crawler required?
 How does web crawler work?
 Crawling strategies
        Breadth first search traversal
        Depth first search traversal
 Architecture of web crawler
 Crawling policies
 Distributed crawling
 Selection Policy that states which pages to
  download.
 Re-visit Policy that states when to check for
  changes to the pages.
 Politeness Policy that states how to avoid
  overloading Web sites.
 Parallelization Policy that states how to
  coordinate distributed Web crawlers.
    Search engines covers only a fraction of Internet.
    This requires download of relevant pages, hence a
    good selection policy is very important.
    Common Selection policies:
        Restricting followed links
        Path-ascending crawling
        Focused crawling
        Crawling the Deep Web
   Web is dynamic; crawling takes a long time.
   Cost factors play important role in crawling.
   Freshness and Age- commonly used cost functions.
   Objective of crawler- high average freshness;
    low average age of web pages.
    Two re-visit policies:
       Uniform policy
       Proportional policy
   Crawlers can have a crippling impact on the
    overall performance of a site.
   The costs of using Web crawlers include:
        Network resources
        Server overload
        Server/ router crashes
        Network and server disruption
   A partial solution to these problems is the robots
    exclusion protocol.
 How to control those robots!
 Web sites and pages can specify that robots
 should not crawl/index certain areas.
 Two components:
    Robots Exclusion Protocol (robots.txt): Site wide
     specification of excluded directories.
    Robots META Tag: Individual document tag to
     exclude indexing or following links.
 Site   administrator puts a “robots.txt” file at
    the root of the host’s web directory.
       http://www.ebay.com/robots.txt
       http://www.cnn.com/robots.txt
       http://clgiles.ist.psu.edu/robots.txt
 File  is a list of excluded directories for a
    given robot (user-agent).
    Exclude all robots from the entire site:
       User-agent: *
      Disallow: /
    New Allow:

   Find some interesting robots.txt
 Exclude   specific directories:
 User-agent: *
  Disallow: /tmp/
  Disallow: /cgi-bin/
  Disallow: /users/paranoid/
 Exclude   a specific robot:
   User-agent: GoogleBot
   Disallow: /
 Allow   a specific robot:
   User-agent: GoogleBot
   Disallow:

   User-agent: *
   Disallow: /
 Only use blank lines to separate different
  User-agent disallowed directories.
 One directory per “Disallow” line.
 No regex (regular expression) patterns in
  directories.
   The crawler runs multiple processes in parallel.
   The goal is:
      To maximize the download rate.
      To minimize the overhead from parallelization.
      To avoid repeated downloads of the same page.

   The crawling system requires a policy for assigning
    the new URLs discovered during the crawling
    process.
 What   is a web crawler?
 Why  is web crawler required?
 How does web crawler work?
 Mechanism used
       Breadth first search traversal
        Depth first search traversal
 Architecture of web crawler
 Crawling policies
 Distributed crawling
   A distributed computing technique whereby
    search engines employ many computers to index
    the Internet via web crawling.

   The idea is to spread out the required resources
    of computation and bandwidth to many
    computers and networks.

   Types of distributed web crawling:
     1. Dynamic Assignment
     2. Static Assignment
 With this, a central server assigns new URLs to
  different crawlers dynamically. This allows the
  central server dynamically balance the load of
  each crawler.
 Configurations of crawling architectures with
  dynamic assignments:
• A small crawler configuration, in which there is
  a central DNS resolver and central queues per
  Web site, and distributed down loaders.
• A large crawler configuration, in which the DNS
  resolver and the queues are also distributed.
• Here a fixed rule is stated from the beginning of
    the crawl that defines how to assign new URLs to
    the crawlers.
•   A hashing function can be used to transform URLs
    into a number that corresponds to the index of
    the corresponding crawling process.
•   To reduce the overhead due to the exchange of
    URLs between crawling processes, when links
    switch from one website to another, the
    exchange should be done in batch.
 Focused crawling was first introduced by
  Chakrabarti.
 A focused crawler ideally would like to download
  only web pages that are relevant to a particular
  topic and avoid downloading all others.
 It assumes that some labeled examples of
  relevant and not relevant pages are available.
   A focused crawler predict the probability that a
    link to a particular page is relevant before
    actually downloading the page. A possible
    predictor is the anchor text of links.

   In another approach, the relevance of a page is
    determined after downloading its content.
    Relevant pages are sent to content indexing and
    their contained URLs are added to the crawl
    frontier; pages that fall below a relevance
    threshold are discarded.
 Yahoo! Slurp: Yahoo Search crawler.
 Msnbot: Microsoft's Bing web crawler.
 Googlebot : Google’s web crawler.
 WebCrawler : Used to build the first publicly-
  available full-text index of a subset of the Web.
 World Wide Web Worm : Used to build a simple
  index of document titles and URLs.
 Web Fountain: Distributed, modular crawler
  written in C++.
 Slug: Semantic web crawler
1)Draw a neat labeled diagram to explain how does a
  web crawler work?
2)What is the function of crawler?
3)How does the crawler knows if it can crawl and index
  data from website? Explain.
4)Write a note on robot.txt.
5)Discuss the architecture of a search engine.
7)Explain difference between crawler and focused
  crawler.
Web crawler

More Related Content

What's hot (20)

Information retrieval-systems notes
Information retrieval-systems notesInformation retrieval-systems notes
Information retrieval-systems notes
 
Search Engines
Search EnginesSearch Engines
Search Engines
 
Open source search engine
Open source search engineOpen source search engine
Open source search engine
 
Web scraping
Web scrapingWeb scraping
Web scraping
 
Web mining
Web miningWeb mining
Web mining
 
Web search vs ir
Web search vs irWeb search vs ir
Web search vs ir
 
What is web scraping?
What is web scraping?What is web scraping?
What is web scraping?
 
Google Search Engine
Google Search Engine Google Search Engine
Google Search Engine
 
Web data mining
Web data miningWeb data mining
Web data mining
 
Web content mining
Web content miningWeb content mining
Web content mining
 
Boolean,vector space retrieval Models
Boolean,vector space retrieval Models Boolean,vector space retrieval Models
Boolean,vector space retrieval Models
 
CS8080 IRT UNIT I NOTES.pdf
CS8080 IRT UNIT I  NOTES.pdfCS8080 IRT UNIT I  NOTES.pdf
CS8080 IRT UNIT I NOTES.pdf
 
GOOGLE FILE SYSTEM
GOOGLE FILE SYSTEMGOOGLE FILE SYSTEM
GOOGLE FILE SYSTEM
 
Web mining slides
Web mining slidesWeb mining slides
Web mining slides
 
Text MIning
Text MIningText MIning
Text MIning
 
Components of a search engine
Components of a search engineComponents of a search engine
Components of a search engine
 
Google File System
Google File SystemGoogle File System
Google File System
 
Semantic Web
Semantic WebSemantic Web
Semantic Web
 
Web Mining Presentation Final
Web Mining Presentation FinalWeb Mining Presentation Final
Web Mining Presentation Final
 
Search Engine
Search EngineSearch Engine
Search Engine
 

Similar to Web crawler

Smart Crawler: A Two Stage Crawler for Concept Based Semantic Search Engine.
Smart Crawler: A Two Stage Crawler for Concept Based Semantic Search Engine.Smart Crawler: A Two Stage Crawler for Concept Based Semantic Search Engine.
Smart Crawler: A Two Stage Crawler for Concept Based Semantic Search Engine.iosrjce
 
Research on Key Technology of Web Reptile
Research on Key Technology of Web ReptileResearch on Key Technology of Web Reptile
Research on Key Technology of Web ReptileIRJESJOURNAL
 
A Novel Interface to a Web Crawler using VB.NET Technology
A Novel Interface to a Web Crawler using VB.NET TechnologyA Novel Interface to a Web Crawler using VB.NET Technology
A Novel Interface to a Web Crawler using VB.NET TechnologyIOSR Journals
 
Smart Crawler Automation with RMI
Smart Crawler Automation with RMISmart Crawler Automation with RMI
Smart Crawler Automation with RMIIRJET Journal
 
Search engine and web crawler
Search engine and web crawlerSearch engine and web crawler
Search engine and web crawlervinay arora
 
[LvDuit//Lab] Crawling the web
[LvDuit//Lab] Crawling the web[LvDuit//Lab] Crawling the web
[LvDuit//Lab] Crawling the webVan-Duyet Le
 
IRJET - Review on Search Engine Optimization
IRJET - Review on Search Engine OptimizationIRJET - Review on Search Engine Optimization
IRJET - Review on Search Engine OptimizationIRJET Journal
 
Web Mining.pptx
Web Mining.pptxWeb Mining.pptx
Web Mining.pptxScrbifPt
 
The Research on Related Technologies of Web Crawler
The Research on Related Technologies of Web CrawlerThe Research on Related Technologies of Web Crawler
The Research on Related Technologies of Web CrawlerIRJESJOURNAL
 
Sekhon final 1_ppt
Sekhon final 1_pptSekhon final 1_ppt
Sekhon final 1_pptManant Sweet
 
SMART CRAWLER: A TWO-STAGE CRAWLER FOR EFFICIENTLY HARVESTING DEEP-WEB INTERF...
SMART CRAWLER: A TWO-STAGE CRAWLER FOR EFFICIENTLY HARVESTING DEEP-WEB INTERF...SMART CRAWLER: A TWO-STAGE CRAWLER FOR EFFICIENTLY HARVESTING DEEP-WEB INTERF...
SMART CRAWLER: A TWO-STAGE CRAWLER FOR EFFICIENTLY HARVESTING DEEP-WEB INTERF...CloudTechnologies
 
Web Crawling Using Location Aware Technique
Web Crawling Using Location Aware TechniqueWeb Crawling Using Location Aware Technique
Web Crawling Using Location Aware Techniqueijsrd.com
 

Similar to Web crawler (20)

webcrawler.pptx
webcrawler.pptxwebcrawler.pptx
webcrawler.pptx
 
Web crawler
Web crawlerWeb crawler
Web crawler
 
Seminar on crawler
Seminar on crawlerSeminar on crawler
Seminar on crawler
 
Smart Crawler: A Two Stage Crawler for Concept Based Semantic Search Engine.
Smart Crawler: A Two Stage Crawler for Concept Based Semantic Search Engine.Smart Crawler: A Two Stage Crawler for Concept Based Semantic Search Engine.
Smart Crawler: A Two Stage Crawler for Concept Based Semantic Search Engine.
 
E017624043
E017624043E017624043
E017624043
 
Research on Key Technology of Web Reptile
Research on Key Technology of Web ReptileResearch on Key Technology of Web Reptile
Research on Key Technology of Web Reptile
 
A Novel Interface to a Web Crawler using VB.NET Technology
A Novel Interface to a Web Crawler using VB.NET TechnologyA Novel Interface to a Web Crawler using VB.NET Technology
A Novel Interface to a Web Crawler using VB.NET Technology
 
Smart Crawler Automation with RMI
Smart Crawler Automation with RMISmart Crawler Automation with RMI
Smart Crawler Automation with RMI
 
Web crawling
Web crawlingWeb crawling
Web crawling
 
Search engine and web crawler
Search engine and web crawlerSearch engine and web crawler
Search engine and web crawler
 
[LvDuit//Lab] Crawling the web
[LvDuit//Lab] Crawling the web[LvDuit//Lab] Crawling the web
[LvDuit//Lab] Crawling the web
 
WebCrawler
WebCrawlerWebCrawler
WebCrawler
 
IRJET - Review on Search Engine Optimization
IRJET - Review on Search Engine OptimizationIRJET - Review on Search Engine Optimization
IRJET - Review on Search Engine Optimization
 
Web Mining.pptx
Web Mining.pptxWeb Mining.pptx
Web Mining.pptx
 
The Research on Related Technologies of Web Crawler
The Research on Related Technologies of Web CrawlerThe Research on Related Technologies of Web Crawler
The Research on Related Technologies of Web Crawler
 
Sekhon final 1_ppt
Sekhon final 1_pptSekhon final 1_ppt
Sekhon final 1_ppt
 
SMART CRAWLER: A TWO-STAGE CRAWLER FOR EFFICIENTLY HARVESTING DEEP-WEB INTERF...
SMART CRAWLER: A TWO-STAGE CRAWLER FOR EFFICIENTLY HARVESTING DEEP-WEB INTERF...SMART CRAWLER: A TWO-STAGE CRAWLER FOR EFFICIENTLY HARVESTING DEEP-WEB INTERF...
SMART CRAWLER: A TWO-STAGE CRAWLER FOR EFFICIENTLY HARVESTING DEEP-WEB INTERF...
 
Web Crawling Using Location Aware Technique
Web Crawling Using Location Aware TechniqueWeb Crawling Using Location Aware Technique
Web Crawling Using Location Aware Technique
 
Web crawler
Web crawlerWeb crawler
Web crawler
 
Seo and analytics basics
Seo and analytics basicsSeo and analytics basics
Seo and analytics basics
 

Recently uploaded

ENGLISH6-Q4-W3.pptxqurter our high choom
ENGLISH6-Q4-W3.pptxqurter our high choomENGLISH6-Q4-W3.pptxqurter our high choom
ENGLISH6-Q4-W3.pptxqurter our high choomnelietumpap1
 
AMERICAN LANGUAGE HUB_Level2_Student'sBook_Answerkey.pdf
AMERICAN LANGUAGE HUB_Level2_Student'sBook_Answerkey.pdfAMERICAN LANGUAGE HUB_Level2_Student'sBook_Answerkey.pdf
AMERICAN LANGUAGE HUB_Level2_Student'sBook_Answerkey.pdfphamnguyenenglishnb
 
Grade 9 Q4-MELC1-Active and Passive Voice.pptx
Grade 9 Q4-MELC1-Active and Passive Voice.pptxGrade 9 Q4-MELC1-Active and Passive Voice.pptx
Grade 9 Q4-MELC1-Active and Passive Voice.pptxChelloAnnAsuncion2
 
Employee wellbeing at the workplace.pptx
Employee wellbeing at the workplace.pptxEmployee wellbeing at the workplace.pptx
Employee wellbeing at the workplace.pptxNirmalaLoungPoorunde1
 
Framing an Appropriate Research Question 6b9b26d93da94caf993c038d9efcdedb.pdf
Framing an Appropriate Research Question 6b9b26d93da94caf993c038d9efcdedb.pdfFraming an Appropriate Research Question 6b9b26d93da94caf993c038d9efcdedb.pdf
Framing an Appropriate Research Question 6b9b26d93da94caf993c038d9efcdedb.pdfUjwalaBharambe
 
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPTECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPTiammrhaywood
 
Romantic Opera MUSIC FOR GRADE NINE pptx
Romantic Opera MUSIC FOR GRADE NINE pptxRomantic Opera MUSIC FOR GRADE NINE pptx
Romantic Opera MUSIC FOR GRADE NINE pptxsqpmdrvczh
 
AmericanHighSchoolsprezentacijaoskolama.
AmericanHighSchoolsprezentacijaoskolama.AmericanHighSchoolsprezentacijaoskolama.
AmericanHighSchoolsprezentacijaoskolama.arsicmarija21
 
Alper Gobel In Media Res Media Component
Alper Gobel In Media Res Media ComponentAlper Gobel In Media Res Media Component
Alper Gobel In Media Res Media ComponentInMediaRes1
 
Gas measurement O2,Co2,& ph) 04/2024.pptx
Gas measurement O2,Co2,& ph) 04/2024.pptxGas measurement O2,Co2,& ph) 04/2024.pptx
Gas measurement O2,Co2,& ph) 04/2024.pptxDr.Ibrahim Hassaan
 
Procuring digital preservation CAN be quick and painless with our new dynamic...
Procuring digital preservation CAN be quick and painless with our new dynamic...Procuring digital preservation CAN be quick and painless with our new dynamic...
Procuring digital preservation CAN be quick and painless with our new dynamic...Jisc
 
ECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptx
ECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptxECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptx
ECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptxiammrhaywood
 
How to Configure Email Server in Odoo 17
How to Configure Email Server in Odoo 17How to Configure Email Server in Odoo 17
How to Configure Email Server in Odoo 17Celine George
 
Introduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher EducationIntroduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher Educationpboyjonauth
 
Hierarchy of management that covers different levels of management
Hierarchy of management that covers different levels of managementHierarchy of management that covers different levels of management
Hierarchy of management that covers different levels of managementmkooblal
 
Introduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxIntroduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxpboyjonauth
 
Full Stack Web Development Course for Beginners
Full Stack Web Development Course  for BeginnersFull Stack Web Development Course  for Beginners
Full Stack Web Development Course for BeginnersSabitha Banu
 
Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Celine George
 

Recently uploaded (20)

ENGLISH6-Q4-W3.pptxqurter our high choom
ENGLISH6-Q4-W3.pptxqurter our high choomENGLISH6-Q4-W3.pptxqurter our high choom
ENGLISH6-Q4-W3.pptxqurter our high choom
 
AMERICAN LANGUAGE HUB_Level2_Student'sBook_Answerkey.pdf
AMERICAN LANGUAGE HUB_Level2_Student'sBook_Answerkey.pdfAMERICAN LANGUAGE HUB_Level2_Student'sBook_Answerkey.pdf
AMERICAN LANGUAGE HUB_Level2_Student'sBook_Answerkey.pdf
 
Grade 9 Q4-MELC1-Active and Passive Voice.pptx
Grade 9 Q4-MELC1-Active and Passive Voice.pptxGrade 9 Q4-MELC1-Active and Passive Voice.pptx
Grade 9 Q4-MELC1-Active and Passive Voice.pptx
 
Employee wellbeing at the workplace.pptx
Employee wellbeing at the workplace.pptxEmployee wellbeing at the workplace.pptx
Employee wellbeing at the workplace.pptx
 
Framing an Appropriate Research Question 6b9b26d93da94caf993c038d9efcdedb.pdf
Framing an Appropriate Research Question 6b9b26d93da94caf993c038d9efcdedb.pdfFraming an Appropriate Research Question 6b9b26d93da94caf993c038d9efcdedb.pdf
Framing an Appropriate Research Question 6b9b26d93da94caf993c038d9efcdedb.pdf
 
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPTECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
 
Model Call Girl in Bikash Puri Delhi reach out to us at 🔝9953056974🔝
Model Call Girl in Bikash Puri  Delhi reach out to us at 🔝9953056974🔝Model Call Girl in Bikash Puri  Delhi reach out to us at 🔝9953056974🔝
Model Call Girl in Bikash Puri Delhi reach out to us at 🔝9953056974🔝
 
Romantic Opera MUSIC FOR GRADE NINE pptx
Romantic Opera MUSIC FOR GRADE NINE pptxRomantic Opera MUSIC FOR GRADE NINE pptx
Romantic Opera MUSIC FOR GRADE NINE pptx
 
AmericanHighSchoolsprezentacijaoskolama.
AmericanHighSchoolsprezentacijaoskolama.AmericanHighSchoolsprezentacijaoskolama.
AmericanHighSchoolsprezentacijaoskolama.
 
9953330565 Low Rate Call Girls In Rohini Delhi NCR
9953330565 Low Rate Call Girls In Rohini  Delhi NCR9953330565 Low Rate Call Girls In Rohini  Delhi NCR
9953330565 Low Rate Call Girls In Rohini Delhi NCR
 
Alper Gobel In Media Res Media Component
Alper Gobel In Media Res Media ComponentAlper Gobel In Media Res Media Component
Alper Gobel In Media Res Media Component
 
Gas measurement O2,Co2,& ph) 04/2024.pptx
Gas measurement O2,Co2,& ph) 04/2024.pptxGas measurement O2,Co2,& ph) 04/2024.pptx
Gas measurement O2,Co2,& ph) 04/2024.pptx
 
Procuring digital preservation CAN be quick and painless with our new dynamic...
Procuring digital preservation CAN be quick and painless with our new dynamic...Procuring digital preservation CAN be quick and painless with our new dynamic...
Procuring digital preservation CAN be quick and painless with our new dynamic...
 
ECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptx
ECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptxECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptx
ECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptx
 
How to Configure Email Server in Odoo 17
How to Configure Email Server in Odoo 17How to Configure Email Server in Odoo 17
How to Configure Email Server in Odoo 17
 
Introduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher EducationIntroduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher Education
 
Hierarchy of management that covers different levels of management
Hierarchy of management that covers different levels of managementHierarchy of management that covers different levels of management
Hierarchy of management that covers different levels of management
 
Introduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxIntroduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptx
 
Full Stack Web Development Course for Beginners
Full Stack Web Development Course  for BeginnersFull Stack Web Development Course  for Beginners
Full Stack Web Development Course for Beginners
 
Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17
 

Web crawler

  • 2.   Why is web crawler required?  How does web crawler work?  Crawling strategies Breadth first search traversal depth first search traversal  Architecture of web crawler  Crawling policies  Distributed crawling
  • 3. The process or program used by search engines to download pages from the web for later processing by a search engine that will index the downloaded pages to provide fast searches.  A program or automated script which browses the World Wide Web in a methodical, automated manner  also known as web spiders and web robots.  less used names- ants, bots and worms.
  • 4.  What is a web crawler?  How does web crawler work?  Crawling strategies Breadth first search traversal depth first search traversal  Architecture of web crawler  Crawling policies  Distributed crawling
  • 5. Internet has a wide expanse of Information.  Finding relevant information requires an efficient mechanism. Web Crawlers provide that scope to the search engine.
  • 6.  What is a web crawler?  Why is web crawler required?  How does web crawler work?  Crawling strategies Breadth first search traversal depth first search traversal  Architecture of web crawler  Crawling policies  Distributed crawling
  • 7.  It starts with a list of URLs to visit, called the seeds . As the crawler visits these URLs, it identifies all the hyperlinks in the page and adds them to the list of visited URLs, called the crawl frontier  URLs from the frontier are recursively visited according to a set of policies.
  • 8. New url’s can be specified here. This is google’s web Crawler.
  • 9. Initialize queue (Q) with initial set of known URL’s. Until Q empty or page or time limit exhausted: Pop URL, L, from front of Q. If L is not an HTML page (.gif, .jpeg, .ps, .pdf, .ppt…) exit loop. If already visited L, continue loop(get next url). Download page, P, for L. If cannot download P (e.g. 404 error, robot excluded) exit loop, else. Index P (e.g. add to inverted index or store cached copy). Parse P to obtain list of new links N. Append N to the end of Q.
  • 10.
  • 11.  What is a web crawler?  Why is web crawler required?  How does web crawler work?  Crawling strategies Breadth first search traversal depth first search traversal  Architecture of web crawler  Crawling policies  Distributed crawling
  • 12. Alternate way of looking at the problem.  Web is a huge directed graph, with documents as vertices and hyperlinks as edges.  Need to explore the graph using a suitable graph traversal algorithm.  W.r.t. previous ex: nodes are represented by rectangles and directed edges are drawn as arrows.
  • 13. Given any graph and a set of seeds at which to start, the graph can be traversed using the algorithm 1. Put all the given seeds into the queue; 2. Prepare to keep a list of “visited” nodes (initially empty); 3. As long as the queue is not empty: a. Remove the first node from the queue; b. Append that node to the list of “visited” nodes c. For each edge starting at that node: i. If the node at the end of the edge already appears on the list of “visited” nodes or it is already in the queue, then do nothing more with that edge; ii. Otherwise, append the node at the end of the edge to the end of the queue.
  • 14.
  • 15.  What is a web crawler?  Why is web crawler required?  How does web crawler work?  Crawling strategies Breadth first search traversal Depth first search traversal  Architecture of web crawler  Crawling policies  Parallel crawling
  • 16. Use depth first search (DFS) algorithm • Get the 1st link not visited from the start page • Visit link and get 1st non-visited link • Repeat above step till no non-visited links • Go to next non-visited link in the previous level and repeat 2nd step
  • 17.
  • 18. depth-first goes off into one branch until it reaches a leaf node  not good if the goal node is on another branch  neither complete nor optimal  uses much less space than breadth-first  much fewer visited nodes to keep track of  smaller fringe  breadth-first is more careful by checking all alternatives  complete and optimal  very memory-intensive
  • 19.  What is a web crawler?  Why is web crawler required?  How does web crawler work?  Crawling strategies Breadth first search traversal Depth first search traversal  Architecture of web crawler  Crawling policies  Distributed crawling
  • 20.
  • 21. Doc Robots URL Fingerprint templates set DNS Dup Content URL Parse URL www Seen? Filter Elim Fetch URL Frontier
  • 22.  URL Frontier: containing URLs yet to be fetches in the current crawl. At first, a seed set is stored in URL Frontier, and a crawler begins by taking a URL from the seed set.  DNS: domain name service resolution. Look up IP address for domain names.  Fetch: generally use the http protocol to fetch the URL.  Parse: the page is parsed. Texts (images, videos, and etc.) and Links are extracted.  Content Seen?: test whether a web page with the same content has already been seen at another URL. Need to develop a way to measure the fingerprint of a web page.
  • 23. URL Filter:  Whether the extracted URL should be excluded from the frontier (robots.txt).  URL should be normalized (relative encoding).  en.wikipedia.org/wiki/Main_Page  <a href="/wiki/Wikipedia:General_disclaimer" title="Wikipedia:General disclaimer">Disclaimers</a>  Dup URL Elim: the URL is checked for duplicate elimination.
  • 24.  What is a web crawler?  Why is web crawler required?  How does web crawler work?  Crawling strategies Breadth first search traversal Depth first search traversal  Architecture of web crawler  Crawling policies  Distributed crawling
  • 25.  Selection Policy that states which pages to download.  Re-visit Policy that states when to check for changes to the pages.  Politeness Policy that states how to avoid overloading Web sites.  Parallelization Policy that states how to coordinate distributed Web crawlers.
  • 26. Search engines covers only a fraction of Internet.  This requires download of relevant pages, hence a good selection policy is very important.  Common Selection policies: Restricting followed links Path-ascending crawling Focused crawling Crawling the Deep Web
  • 27. Web is dynamic; crawling takes a long time.  Cost factors play important role in crawling.  Freshness and Age- commonly used cost functions.  Objective of crawler- high average freshness; low average age of web pages.  Two re-visit policies: Uniform policy Proportional policy
  • 28. Crawlers can have a crippling impact on the overall performance of a site.  The costs of using Web crawlers include: Network resources Server overload Server/ router crashes Network and server disruption  A partial solution to these problems is the robots exclusion protocol.
  • 29.  How to control those robots! Web sites and pages can specify that robots should not crawl/index certain areas. Two components:  Robots Exclusion Protocol (robots.txt): Site wide specification of excluded directories.  Robots META Tag: Individual document tag to exclude indexing or following links.
  • 30.  Site administrator puts a “robots.txt” file at the root of the host’s web directory.  http://www.ebay.com/robots.txt  http://www.cnn.com/robots.txt  http://clgiles.ist.psu.edu/robots.txt  File is a list of excluded directories for a given robot (user-agent). Exclude all robots from the entire site: User-agent: * Disallow: / New Allow:  Find some interesting robots.txt
  • 31.  Exclude specific directories: User-agent: * Disallow: /tmp/ Disallow: /cgi-bin/ Disallow: /users/paranoid/  Exclude a specific robot: User-agent: GoogleBot Disallow: /  Allow a specific robot: User-agent: GoogleBot Disallow: User-agent: * Disallow: /
  • 32.  Only use blank lines to separate different User-agent disallowed directories.  One directory per “Disallow” line.  No regex (regular expression) patterns in directories.
  • 33. The crawler runs multiple processes in parallel.  The goal is: To maximize the download rate. To minimize the overhead from parallelization. To avoid repeated downloads of the same page.  The crawling system requires a policy for assigning the new URLs discovered during the crawling process.
  • 34.  What is a web crawler?  Why is web crawler required?  How does web crawler work?  Mechanism used Breadth first search traversal Depth first search traversal  Architecture of web crawler  Crawling policies  Distributed crawling
  • 35.
  • 36. A distributed computing technique whereby search engines employ many computers to index the Internet via web crawling.  The idea is to spread out the required resources of computation and bandwidth to many computers and networks.  Types of distributed web crawling: 1. Dynamic Assignment 2. Static Assignment
  • 37.  With this, a central server assigns new URLs to different crawlers dynamically. This allows the central server dynamically balance the load of each crawler.  Configurations of crawling architectures with dynamic assignments: • A small crawler configuration, in which there is a central DNS resolver and central queues per Web site, and distributed down loaders. • A large crawler configuration, in which the DNS resolver and the queues are also distributed.
  • 38. • Here a fixed rule is stated from the beginning of the crawl that defines how to assign new URLs to the crawlers. • A hashing function can be used to transform URLs into a number that corresponds to the index of the corresponding crawling process. • To reduce the overhead due to the exchange of URLs between crawling processes, when links switch from one website to another, the exchange should be done in batch.
  • 39.  Focused crawling was first introduced by Chakrabarti.  A focused crawler ideally would like to download only web pages that are relevant to a particular topic and avoid downloading all others.  It assumes that some labeled examples of relevant and not relevant pages are available.
  • 40. A focused crawler predict the probability that a link to a particular page is relevant before actually downloading the page. A possible predictor is the anchor text of links.  In another approach, the relevance of a page is determined after downloading its content. Relevant pages are sent to content indexing and their contained URLs are added to the crawl frontier; pages that fall below a relevance threshold are discarded.
  • 41.  Yahoo! Slurp: Yahoo Search crawler.  Msnbot: Microsoft's Bing web crawler.  Googlebot : Google’s web crawler.  WebCrawler : Used to build the first publicly- available full-text index of a subset of the Web.  World Wide Web Worm : Used to build a simple index of document titles and URLs.  Web Fountain: Distributed, modular crawler written in C++.  Slug: Semantic web crawler
  • 42. 1)Draw a neat labeled diagram to explain how does a web crawler work? 2)What is the function of crawler? 3)How does the crawler knows if it can crawl and index data from website? Explain. 4)Write a note on robot.txt. 5)Discuss the architecture of a search engine. 7)Explain difference between crawler and focused crawler.