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印第安纳大学:《Informatics》课程PPT教学课件(信息学)08 网络爬虫 Web Crawling

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• Motivation and taxonomy of crawlers • Basic crawlers and implementation issues • Universal crawlers • Preferential (focused and topical) crawlers • Evaluation of preferential crawlers • Crawler ethics and conflicts • New developments: social, collaborative, federated crawlers
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Ch 8: Web Crawling By Filippo menczer Indiana University School of Informatics in Web data Mining by Bing Liu Springer 2007 informatics

Ch. 8: Web Crawling By Filippo Menczer Indiana University School of Informatics in Web Data Mining by Bing Liu Springer, 2007

Outline Motivation and taxonomy of crawlers Basic crawlers and implementation issues Universal crawlers Preferential (focused and topical)crawlers Evaluation of preferential crawlers Crawler ethics and conflicts New developments: social, collaborative federated crawlers Slides 2007 Filippo Menczer, Indiana University School of Informatics Bing Liu: Web Data Mining. Springer, 200 Ch 8 Web Crawing by Filippo Menczer informatics

Slides © 2007 Filippo Menczer, Indiana University School of Informatics Bing Liu: Web Data Mining. Springer, 2007 Ch. 8 Web Crawling by Filippo Menczer Outline • Motivation and taxonomy of crawlers • Basic crawlers and implementation issues • Universal crawlers • Preferential (focused and topical) crawlers • Evaluation of preferential crawlers • Crawler ethics and conflicts • New developments: social, collaborative, federated crawlers

Google Search: spears Web Images Groups New Froome more. Google C Search) Ar ererecesea Resutts 1-10 of about 9, 440, 000 for spear nt on. (0.14 seconds) News results for spears- Vien oad.1 novr Inbune-7 hours ago al things Britney.… Q: How does a Britney Spears ve Records search engine know that all ms, and much more! these pages contain the to Bntney win the most active s9y:间p,5mm query terms? bntneyspears. org-7BK Britney A: Because all of those pages Mystery of Britner's Breasts Eys breasts.35·28-hd· S-ar pao have been Britney Spears speling correction pangs detected by ou spe ng correcton system bruney siney.htm-40k· ached-Sme pages… www.googe.comobs crawled s music Britney Spears Mrics s music fun games chat lyrics what is nice the Bntney Spears forun www.briney-spears.com-42<-jun14,2004-cached-smiarpapes Britney Spears Zone. Your Guide to Britney Pictures and News www.brtneyzone.com/-101k-jun14,2004-ca Slides 2007 Filippo Menczer, Indiana University School of Informatics Bing Liu: Web Data Mining. Springer, 200 Ch 8 Web Crawing by Filippo Menczer informatics

Slides © 2007 Filippo Menczer, Indiana University School of Informatics Bing Liu: Web Data Mining. Springer, 2007 Ch. 8 Web Crawling by Filippo Menczer Q: How does a search engine know that all these pages contain the query terms? A: Because all of those pages have been crawled

YAHOO!F cn ADE YAHOOI Speakeasy- Band &m Britney Spears Ant st Page Speaker Junkies-mest Spear of Destinv-inclu SHOO! Entertainment Spearhead图 CATEGORIES Spearmint- official site Spearritt, Hannah 7) Spears, Britney(63) D>上的mM SITE USTINGS othe w的 o just this The- inc Most Popular Crawler d- Wasat Bntney Spoars-offical site win chat nev.com-jiverEcords'official INSIDE YAHOOI · Special EFX( LAUNCH Music: chek out wais vew, aes, a basic idea 目量. Slides 2007 Filippo Menczer, Indiana University School of Informatics Bing Liu: Web Data Mining. Springer, 200 Ch 8 Web Crawing by Filippo Menczer infos

Slides © 2007 Filippo Menczer, Indiana University School of Informatics Bing Liu: Web Data Mining. Springer, 2007 Ch. 8 Web Crawling by Filippo Menczer Crawler: basic idea starting pages (seeds)

Many names Crawler spider Robot(or bot) Web agent Wanderer, worm And famous instances: googlebot scooter, slurp, msnbot Slides 2007 Filippo Menczer, Indiana University School of Informatics Indiana University School of Bing Liu: Web Data Mining. Springer, 200 Ch 8 Web Crawing by Filippo Menczer Informatics

Slides © 2007 Filippo Menczer, Indiana University School of Informatics Bing Liu: Web Data Mining. Springer, 2007 Ch. 8 Web Crawling by Filippo Menczer Many names • Crawler • Spider • Robot (or bot) • Web agent • Wanderer, worm, … • And famous instances: googlebot, scooter, slurp, msnbot, …

Googlebot you eee tcsh-961 homer:-%more/var/og/httpd/access_log 129.217.55.111--[11/ep/2004:04:36:24-0500]"GET/fil/ Thanksgiving/1999/ Pages/ Image1. html Http/1.0”200302 84.135.208.173--[1 Max/2000/fall/november/ Http/1. 1"404 320 88.100.20.198-[11/Sep/2004:04:41:40-0500]"GET/-fil/Max/2000/Fall/ November/HP/1.0”404308 64.68.82,182--[11/ep/2004:04:41:51-0500]"GET/ robots, txt Http/1.0”404290 62.39.213.35 2004:04 00]get/-fil/max/2000/falL/november/http:/1.0"404308 [11/Sep/2004:04:41:52-0500]"GET/network/network.mapHTTP/1.0”2003544 129,217.55.11 [11/Sep/2004:04:41:58-050]"GET /maX/2003/fall/fall-pages/image3. html Http/1. 0"200 491 129.217.55.111-[11/Sep/2004:04:42:01-0500]"GET /mAX/2002/spring/spring-pages/image6. html Http/1. 0"200 495 /maX/2002/europe0z/crans-montana/ Http/1.0"200 6361 129. 217.55. 111--[11/sep/2004: 04: 42: 36-0500get /-fil/acation/Europe02/venezia/pages/image 12. html Http/1.0"200 352 129.217.55.111--[11/Sep/2004:04:43:01-0500]"GET Thanksgiving/1999/pages/image9. html Http/1.0"200 301 129.217.55.111--[11/sep/2004:04:43:43-050]"GET/~fil/Max/2003/FalL/Fall- pages/ Image2. html htTp/1.0"200485 129.217.55.111 [11/5ep/2004:04:43:45-050]"GET Max/2002/Spring/Spring s/image5. html Http/1.0"200 498 129.217.55.111--[11/sep/2004:04:43:48-0500]"GET/~fil/ax/200/ Europeo2/ Bologna/HTP/1.0”2002469 129. 217.55. 111--[11/sep/2004: 04: 44: 14-0500]get /-fil/vacation/europe02/venezia/pages/imagell. html Http/1. 0"200 352 129.217.55.111 [11/sep/2004: 04: 44: 49-0500]"get /-fil/thanksgiving/1999/paGes/imaGe8. html Http/1. 0"200 301 129.217.55.111--[11/Sep/2004:04:45:30-0500]"GET MMax/2003/FalL/FaLl-Po html Http/1.0"200485 129.217.55.111--[11/sep/2004:04:45:31-0500]"GET/fil/Max/2002/ Spring/ Spring- Pages/ Image4. html Http/1.0”200501 129. 217.55.111--[11/sep/2004: 04: 45: 57-0500]"get /-fil/acation/europe0z/venezia/pages/image 10. htmL Http/1.0"200 352 129.217.55,111--11/sep/2004:04:46:25-0590]"GET /thaNksgiving/1999/pages/image7. html htTp/1.0"200 301 129.217.55.111-[11/sep/2004:04:50:27-0590]"GET Max/2003/fall/fall-pages/image0. html Http/1.0"200 495 129.217.55.111-[11/ep/2004:04:50:30-0500]"GET MAX/2002/spring/spring-pages/imagE3. html Http/1.0"200501 129. 217.55. 111--[11/sep/2004: 04: 50: 59-0500]get /-fil/vacation/europE02/venezia/pages/image9. html Http/1.0"200 318 129.217.55.111-[11/sep/2004:04:51:32-0500]"GET/-fil/ Thanksgiving/1999/ Pages/ Image6. html Http/1.0”208381 [11/sep/2004: 04: 52: 40-0500]"get /-fil/max/2002/sprinG/spring-pages/image2. html Http/1.0"200 522 homer:-%host64.68.82.182 182.82. 68. 64 in-addr. arpa domain name pointer crawler 14 googlebot. com Slides 2007 Filippo Menczer, Indiana University School of Informatics Bing Liu: Web Data Mining. Springer, 200 Ch 8 Web Crawing by Filippo Menczer informatics

Slides © 2007 Filippo Menczer, Indiana University School of Informatics Bing Liu: Web Data Mining. Springer, 2007 Ch. 8 Web Crawling by Filippo Menczer Googlebot & you

Motivation for crawlers Support universal search engines(Google, yahoo, MSN/Windows Live, Ask, etc.) Vertical(specialized) search engines, e. g news, shopping papers, recipes, reviews, etc Business intelligence: keep track of potential competitors partners Monitor Web sites of interest Evil: harvest emails for spamming, phishing Can you think of some others? Slides 2007 Filippo Menczer, Indiana University School of Informatics Bing Liu: Web Data Mining. Springer, 200 Ch 8 Web Crawing by Filippo Menczer informatics

Slides © 2007 Filippo Menczer, Indiana University School of Informatics Bing Liu: Web Data Mining. Springer, 2007 Ch. 8 Web Crawling by Filippo Menczer Motivation for crawlers • Support universal search engines (Google, Yahoo, MSN/Windows Live, Ask, etc.) • Vertical (specialized) search engines, e.g. news, shopping, papers, recipes, reviews, etc. • Business intelligence: keep track of potential competitors, partners • Monitor Web sites of interest • Evil: harvest emails for spamming, phishing… • … Can you think of some others?…

a crawler within a search engine Web Page → repository googlebot Google Text link Query analysIs 四a= G oo8 hits Text index Page Rank Ranker Slides 2007 Filippo Menczer, Indiana University School of Informatics Bing Liu: Web Data Mining. Springer, 200 Ch 8 Web Crawing by Filippo Menczer informatics

Slides © 2007 Filippo Menczer, Indiana University School of Informatics Bing Liu: Web Data Mining. Springer, 2007 Ch. 8 Web Crawling by Filippo Menczer A crawler within a search engine Web Text index PageRank Page repository googlebot Text & link Query analysis hits Ranker

One taxonomy of crawlers Crawlers Universal crawlers Preferential crawlers Focused crawlers Topical crawlers Adaptive topical crawlers Static crawlers Evolutionary crawlers Reinforcement learning crawlers Best-first Page Rank Many other criteria could be used Incremental Interactive, Concurrent Etc Slides 2007 Filippo Menczer, Indiana University School of Informati Bing Liu: Web Data Mining. Springer, 200 Ch 8 Web Crawing by Filippo Menczer informatics

Slides © 2007 Filippo Menczer, Indiana University School of Informatics Bing Liu: Web Data Mining. Springer, 2007 Ch. 8 Web Crawling by Filippo Menczer One taxonomy of crawlers Universal crawlers Focused crawlers Evolutionary crawlers Reinforcement learning crawlers etc... Adaptive topical crawlers Best-first PageRank etc... Static crawlers Topical crawlers Preferential crawlers Crawlers • Many other criteria could be used: – Incremental, Interactive, Concurrent, Etc

Outline Motivation and taxonomy of crawlers Basic crawlers and implementation issues Universal crawlers Preferential (focused and topical)crawlers Evaluation of preferential crawlers Crawler ethics and conflicts New developments: social, collaborative federated crawlers Slides 2007 Filippo Menczer, Indiana University School of Informatics Bing Liu: Web Data Mining. Springer, 200 Ch 8 Web Crawing by Filippo Menczer informatics

Slides © 2007 Filippo Menczer, Indiana University School of Informatics Bing Liu: Web Data Mining. Springer, 2007 Ch. 8 Web Crawling by Filippo Menczer Outline • Motivation and taxonomy of crawlers • Basic crawlers and implementation issues • Universal crawlers • Preferential (focused and topical) crawlers • Evaluation of preferential crawlers • Crawler ethics and conflicts • New developments: social, collaborative, federated crawlers

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