Back to Results
First PageMeta Content
Web crawlers / Networks / Social networks / Copying mechanism / Barabási–Albert model / Network topology / Semantic similarity / Cluster analysis / Focused crawler / Graph theory / Statistics / Mathematics


Growing and navigating the small world Web by local content Filippo Menczer† Department of Management Sciences, University of Iowa, Iowa City, IA[removed]Edited by Elwyn R. Berlekamp, University of California, Berkeley,
Add to Reading List

Document Date: 2011-12-04 14:11:42


Open Document

File Size: 211,71 KB

Share Result on Facebook

City

San Francisco / New York / Iowa City / Berlin / Cambridge / /

Company

Fiat / Tomkins / Neural Information Processing Systems / Kraft / MIT Press / COMPUTER SCIENCES / F. (2002) Autonomous Agents Multi-Agent Systems / Yahoo / /

Country

United States / United Kingdom / /

/

Facility

University of Iowa / University of California / /

IndustryTerm

power-law degree distribution / decentralized Web navigation algorithm / power-law distribution / Web search tools / Web content / Web link topology / decentralized Web navigation algorithms / navigation algorithms / power-law topology / large Web sample / social small world networks / Web page degree / decentralized crawling algorithms / cases navigation algorithms / decentralized Web crawlers / Web degree distributions / geographic networks / Web Conference / source Web / crawling algorithm / Web topology / actual Web directories / decentralized search tools / universal search engines / realistic Web / Web dimensionality / link兾lexical power law relationship / content-driven Web crawlers / hierarchical networks / polylogarithmic navigation algorithms / Web communities / search engine technology / actual Web navigation / power-law degree distributions / power law exponents / greedy algorithms / potential Web applications / search tools / Web Navigation Background / Web hypertext degree / important applications / greedy algorithm / search engines / inverse power-law dependence / power law model / real Web crawler / Web degree / power law / power-law model / Web graph / Web authors / power-law tail / search engine / massive Web crawls / Web crawler / Web crawlers / Web lexical similarity / decentralized algorithms / /

Organization

National Science Foundation / Association for Computing Machinery Symposium / MIT / Cambridge Univ. / University of California / Berkeley / Association for Computing Machinery / Filippo Menczer† Department of Management Sciences / Silver Spring / University of Iowa / IEEE Computer Society / /

Person

Christos Papadimitriou / Lada Adamic / Silver Spring / Filippo Menczer / Jon Kleinberg / Gautam Pant / Alberto Segre / Morgan Kaufmann / Rik Belew / Mark Newman / Pr / /

Position

D. J. / exponential model / geographic model / Harper / D. J. / author / model / power law model / representative / candidate for r / /

ProvinceOrState

New York / California / Iowa / /

PublishedMedium

Physica A / Machine Learning / Theory of Computing / Lecture Notes in Computer Science / /

Technology

decentralized Web navigation algorithm / search engine / search engine technology / polylogarithmic navigation algorithms / Machine Learning / PDF / navigation algorithms / cases navigation algorithms / greedy algorithm / decentralized Web navigation algorithms / http / simulation / crawling algorithms / Content-Based Crawling Algorithms / decentralized crawling algorithms / /

URL

www.pnas.org兾cgi兾doi兾10.1073兾pnas.212348399 / /

SocialTag